Electronics and communications engineering Books

Book SynopsisUnderstand the mechanics of wireless communication Wireless Communications: Principles, Theory and Methodology offers a detailed introduction to the technology. Comprehensive and well-rounded coverage includes signaling, transmission, and detection, including the mathematical and physics principles that underlie the technology''s mechanics. Problems with modern wireless communication are discussed in the context of applied skills, and the various approaches to solving these issues offer students the opportunity to test their understanding in a practical manner. With in-depth explanations and a practical approach to complex material, this book provides students with a clear understanding of wireless communication technology.Table of ContentsPreface xvii Acknowledgments xix 1 Introduction 1 1.1 Resources for wireless communications 3 1.2 Shannon’s theory 3 1.3 Three challenges 4 1.4 Digital modulation versus coding 5 1.5 Philosophy to combat interference 6 1.6 Evolution of processing strategy 7 1.7 Philosophy to exploit two-dimensional random fields 7 1.8 Cellular: Concept, Evolution, and 5G 8 1.9 The structure of this book 10 1.10 Repeatedly used abbreviations and math symbols 10 Problems 12 References 12 2 Mathematical Background 14 2.1 Introduction 14 2.2 Congruence mapping and signal spaces 14 2.3 Estimation methods 19 2.3.1 Maximum likelihood estimation (MLE) 20 2.3.2 Maximum a posteriori estimation 21 2.4 Commonly used distributions in wireless 21 2.4.1 Chi-square distributions 21 2.4.2 Gamma distribution 25 2.4.3 Nakagami distribution 26 2.4.4 Wishart distribution 26 2.5 The calculus of variations 28 2.6 Two inequalities for optimization 29 2.6.1 Inequality for Rayleigh quotient 29 2.6.2 Hadamard inequality 29 2.7 Q-function 30 2.8 The CHF method and its skilful applications 32 2.8.1 Gil-Pelaez’s lemma 32 2.8.2 Random variables in denominators 32 2.8.3 Parseval’s theorem 33 2.9 Matrix operations and differentiation 33 2.9.1 Decomposition of a special determinant 33 2.9.2 Higher order derivations 33 2.9.3 Kronecker product 34 2.10 Additional reading 34 Problems 34 References 35 3 Channel Characterization 37 3.1 Introduction 37 3.2 Large-scale propagation loss 38 3.2.1 Free-space propagation 39 3.2.2 Average large-scale path loss in mobile 40 3.2.3 Okumura’s model 40 3.2.4 Hata’s model 42 3.2.5 JTC air model 42 3.3 Lognormal shadowing 43 3.4 Multipath characterization for local behavior 44 3.4.1 An equivalent bandwidth 44 3.4.2 Temporal evolution of path coefficients 49 3.4.3 Statistical description of local fluctuation 50 3.4.4 Complex Gaussian distribution 50 3.4.5 Nakagami fading 51 3.4.6 Clarke–Jakes model 52 3.5 Composite model to incorporate multipath and shadowing 53 3.6 Example to illustrate the use of various models 54 3.6.1 Static design 54 3.6.2 Dynamic design 55 3.6.3 Large-scale design 56 3.7 Generation of correlated fading channels 56 3.7.1 Rayleigh fading with given covariance structure 56 3.7.2 Correlated Nakagami fading 57 3.7.3 Complex correlated Nakagami channels 62 3.7.4 Correlated lognormal shadowing 62 3.7.5 Fitting a lognormal sum 64 3.8 Summary 65 3.9 Additional reading 66 Problems 66 References 68 4 Digital Modulation 70 4.1 Introduction 70 4.2 Signals and signal space 71 4.3 Optimal MAP and ML receivers 72 4.4 Detection of two arbitrary waveforms 74 4.5 MPSK 77 4.5.1 BPSK 77 4.5.2 QPSK 79 4.5.3 MPSK 81 4.6 M-ary QAM 85 4.7 Noncoherent scheme–differential MPSK 88 4.7.1 Differential BPSK 88 4.7.2 Differential MPSK 89 4.7.3 Connection to MPSK 89 4.8 MFSK 90 4.8.1 BFSK with coherent detection 90 4.9 Noncoherent MFSK 92 4.10 Bit error probability versus symbol error probability 93 4.10.1 Orthogonal MFSK 93 4.10.2 Square M-QAM 93 4.10.3 Gray-mapped MPSK 94 4.11 Spectral efficiency 96 4.12 Summary of symbol error probability for various schemes 97 4.13 Additional reading 98 Problems 98 References 102 5 Minimum Shift Keying 103 5.1 Introduction 103 5.2 MSK 104 5.3 de Buda’s approach 105 5.3.1 The basic idea and key equations 105 5.4 Properties of MSK signals 106 5.5 Understanding MSK 108 5.5.1 MSK as FSK 108 5.5.2 MSK as offset PSK 109 5.6 Signal space 109 5.7 MSK power spectrum 110 5.8 Alternative scheme–differential encoder 113 5.9 Transceivers for MSK signals 115 5.10 Gaussian-shaped MSK 116 5.11 Massey’s approach to MSK 117 5.11.1 Modulation 117 5.11.2 Receiver structures and error performance 117 5.12 Summary 119 Problems 119 References 120 6 Channel Coding 121 6.1 Introduction and philosophical discussion 121 6.2 Preliminary of Galois fields 123 6.2.1 Fields 123 6.2.2 Galois fields 124 6.2.3 The primitive element of GF(q) 124 6.2.4 Construction of GF(q) 124 6.3 Linear block codes 126 6.3.1 Syndrome test 129 6.3.2 Error-correcting capability 132 6.4 Cyclic codes 134 6.4.1 The order of elements: a concept in GF(q) 134 6.4.2 Cyclic codes 136 6.4.3 Generator, parity check, and syndrome polynomial 137 6.4.4 Systematic form 138 6.4.5 Syndrome and decoding 140 6.5 Golay code 141 6.6 BCH codes 141 6.6.1 Generating BCH codes 142 6.6.2 Decoding BCH codes 143 6.7 Convolutional codes 146 6.7.1 Examples 146 6.7.2 Code generation 147 6.7.3 Markovian property 148 6.7.4 Decoding with hard-decision Viterbi algorithm 150 6.7.5 Transfer function 152 6.7.6 Choice of convolutional codes 155 6.7.7 Philosophy behind decoding strategies 156 6.7.8 Error performance of convolutional decoding 160 6.8 Trellis-coded modulation 162 6.9 Summary 166 Problems 166 References 170 7 Diversity Techniques 171 7.1 Introduction 171 7.2 Idea behind diversity 173 7.3 Structures of various diversity combiners 174 7.3.1 MRC 174 7.3.2 EGC 175 7.3.3 SC 176 7.4 PDFs of output SNR 176 7.4.1 MRC 176 7.4.2 EGC 178 7.4.3 SC 178 7.5 Average SNR comparison for various schemes 179 7.5.1 MRC 179 7.5.2 EGC 180 7.5.3 SC 181 7.6 Methods for error performance analysis 182 7.6.1 The chain rule 182 7.6.2 The CHF method 183 7.7 Error probability of MRC 183 7.7.1 Error performance in nondiversity Rayleigh fading 183 7.7.2 MRC in i.i.d. Rayleigh fading 185 7.7.3 MRC in correlated Rayleigh fading 187 7.7.4 Pe for generic channels 188 7.8 Error probability of EGC 189 7.8.1 Closed-form solution to order-3 EGC 189 7.8.2 General EGC error performance 191 7.8.3 Diversity order of EGC 192 7.9 Average error performance of SC in Rayleigh fading 193 7.9.1 Pure SC 193 7.9.2 Generalized SC 195 7.10 Performance of diversity MDPSK systems 196 7.10.1 Nondiversity MDPSK in Rayleigh fading 196 7.10.2 Remarks on use of the chain rule 199 7.10.3 Linear prediction to fit the chain rule 199 7.10.4 Alternative approach for diversity MDPSK 200 7.11 Noncoherent MFSK with diversity reception 201 7.12 Summary 203 Problems 204 References 206 8 Processing Strategies for Wireless Systems 209 8.1 Communication problem 209 8.2 Traditional strategy 210 8.3 Paradigm of orthogonality 211 8.4 Turbo processing principle 211 Problems 213 References 213 9 Channel Equalization 214 9.1 Introduction 214 9.2 Pulse shaping for ISI-free transmission 215 9.3 ISI and equalization strategies 216 9.4 Zero-forcing equalizer 217 9.4.1 Orthogonal projection 217 9.4.2 ZFE 219 9.4.3 Equivalent discrete ZFE receiver 221 9.5 MMSE linear equalizer 225 9.6 Decision-feedback equalizer (DFE) 227 9.7 SNR comparison and error performance 229 9.8 An example 230 9.9 Spectral factorization 233 9.10 Summary 234 Problems 234 References 236 10 Channel Decomposition Techniques 238 10.1 Introduction 238 10.2 Channel matrix of ISI channels 239 10.3 Idea of channel decomposition 239 10.4 QR-decomposition-based Tomlinson–Harashima equalizer 240 10.5 The GMD equalizer 242 10.6 OFDM for time-invariant channel 243 10.6.1 Channel SVD 243 10.6.2 OFDM: a multicarrier modulation technique 244 10.6.3 PAPR and statistical behavior of OFDM 246 10.6.4 Combating PAPR 247 10.7 Cyclic prefix and circulant channel matrix 248 10.8 OFDM receiver 251 10.9 Channel estimation 251 10.10 Coded OFDM 252 10.11 Additional reading 252 Problems 252 References 254 11 Turbo Codes and Turbo Principle 257 11.1 Introduction and philosophical discussion 257 11.1.1 Generation of random-like long codes 258 11.1.2 The turbo principle 259 11.2 Two-device mechanism for iteration 259 11.3 Turbo codes 261 11.3.1 A turbo encoder 261 11.3.2 RSC versus NRC 261 11.3.3 Turbo codes with two constituent RSC encoders 264 11.4 BCJR algorithm 266 11.5 Turbo decoding 270 11.6 Illustration of turbo-code performance 270 11.7 Extrinsic information transfer (EXIT) charts 272 11.8 Convergence and fixed points 276 11.9 Statistics of LLRs 277 11.9.1 Mean and variance of LLRs 277 11.9.2 Mean and variance of hard decision 277 11.10 Turbo equalization 278 11.11 Turbo CDMA 281 11.12 Turbo IDMA 283 11.13 Summary 283 Problems 284 References 287 12 Multiple-Access Channels 289 12.1 Introduction 289 12.2 Typical MA schemes 291 12.3 User space of multiple-access 292 12.3.1 User spaces for TDMA 293 12.3.2 User space for CDMA 294 12.3.3 User space for MC-CDMA 294 12.3.4 MC-DS-CDMA 295 12.3.5 User space for OFDMA 296 12.3.6 Unified framework for orthogonal multiaccess schemes 297 12.4 Capacity of multiple-access channels 298 12.4.1 Flat fading 299 12.4.2 Frequency-selective fading 300 12.5 Achievable MI by various MA schemes 301 12.5.1 AWGN channel 301 12.5.2 Flat-fading MA channels 304 12.6 CDMA-IS-95 306 12.6.1 Forward link 306 12.6.2 Reverse link 308 12.7 Processing gain of spreading spectrum 310 12.8 IS-95 downlink receiver and performance 310 12.9 IS-95 uplink receiver and performance 317 12.10 3GPP-LTE uplink 318 12.11 m-Sequences 321 12.11.1 PN sequences of a shorter period 322 12.11.2 Conditions for m-sequence generators 322 12.11.3 Properties of m-sequence 323 12.11.4 Ways to generate PN sequences 324 12.12 Walsh sequences 327 12.13 CAZAC sequences for LTE-A 327 12.14 Nonorthogonal MA schemes 329 12.15 Summary 330 Problems 330 References 334 13 Wireless MIMO Systems 337 13.1 Introduction 337 13.2 Signal model and mutual information 338 13.3 Capacity with CSIT 339 13.4 Ergodic capacity without CSIT 340 13.4.1 i.i.d. MIMO Rayleigh channels 341 13.4.2 Ergodic capacity for correlated MIMO channels 341 13.5 Capacity: asymptotic results 344 13.5.1 Asymptotic capacity with large MIMO 344 13.5.2 Large SNR approximation 345 13.6 Optimal transceivers with CSIT 346 13.6.1 Optimal eigenbeam transceiver 347 13.6.2 Distributions of the largest eigenvalue 348 13.6.3 Average symbol-error probability 350 13.6.4 Average mutual information of MIMO-MRC 350 13.6.5 Average symbol-error probability 351 13.7 Receivers without CSIT 352 13.8 Optimal receiver 352 13.9 Zero-forcing MIMO receiver 353 13.10 MMSE receiver 355 13.11 VBLAST 357 13.11.1 Alternative VBLAST based on QR decomposition 358 13.12 Space–time block codes 359 13.13 Alamouti codes 359 13.13.1 One receive antenna 359 13.13.2 Two receive antennas 360 13.14 General space–time codes 362 13.14.1 Exact pairwise error probability 363 13.15 Information lossless space–time codes 365 13.16 Multiplexing gain versus diversity gain 365 13.16.1 Two frameworks 366 13.16.2 Derivation of the DMT 367 13.16.3 Available DFs for diversity 368 13.17 Summary 370 Problems 370 References 374 14 Cooperative Communications 377 14.1 A historical review 377 14.2 Relaying 378 14.3 Cooperative communications 379 14.3.1 Cooperation protocols 380 14.3.2 Diversity analysis 382 14.3.3 Resource allocation 384 14.4 Multiple-relay cooperation 385 14.4.1 Multi-relay over frequency-selective channels 386 14.4.2 Optimal matrix structure 389 14.4.3 Power allocation 390 14.5 Two-way relaying 395 14.5.1 Average power constraints 397 14.5.2 Instantaneous power constraint 399 14.6 Multi-cell MIMO 400 14.7 Summary 401 Problems 401 References 402 15 Cognitive Radio 405 15.1 Introduction 405 15.2 Spectrum sensing for spectrum holes 406 15.3 Matched filter versus energy detector 407 15.3.1 Matched-filter detection 407 15.3.2 Energy detection 408 15.4 Detection of random primary signals 410 15.4.1 Energy-based detection 411 15.4.2 Maximum likelihood ratio test 412 15.4.3 Eigenvalue ratio test 413 15.5 Detection without exact knowledge of σ2n 414 15.5.1 LRT with σ2n 414 15.5.2 LRT without noise-level reference 415 15.6 Cooperative spectrum sensing 416 15.7 Standardization of CR networks 418 15.8 Experimentation and commercialization of CR systems 418 Problems 419 References 420 Index 423

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Book SynopsisMathematical Foundations of Fuzzy Sets Introduce yourself to the foundations of fuzzy logic with this easy-to-use guide Many fields studied are defined by imprecise information or high degrees of uncertainty. When this uncertainty derives from randomness, traditional probabilistic statistical methods are adequate to address it; more everyday forms of vagueness and imprecision, however, require the toolkit associated with ''fuzzy sets'' and ''fuzzy logic''. Engineering and mathematical fields related to artificial intelligence, operations research and decision theory are now strongly driven by fuzzy set theory. Mathematical Foundations of Fuzzy Sets introduces readers to the theoretical background and practical techniques required to apply fuzzy logic to engineering and mathematical problems. It introduces the mathematical foundations of fuzzy sets as well as the current cutting edge of fuzzy-set operations and arithmetic, offering a roundedTable of ContentsPreface ix 1 Mathematical Analysis 1 1.1 Infimum and Supremum 1 1.2 Limit Inferior and Limit Superior 3 1.3 Semi-Continuity 11 1.4 Miscellaneous 19 2 Fuzzy Sets 23 2.1 Membership Functions 23 2.2 𝛼-level Sets 24 2.3 Types of Fuzzy Sets 34 3 Set Operations of Fuzzy Sets 43 3.1 Complement of Fuzzy Sets 43 3.2 Intersection of Fuzzy Sets 44 3.3 Union of Fuzzy Sets 51 3.4 Inductive and Direct Definitions 56 3.5 𝛼-Level Sets of Intersection and Union 61 3.6 Mixed Set Operations 65 4 Generalized Extension Principle 69 4.1 Extension Principle Based on the Euclidean Space 69 4.2 Extension Principle Based on the Product Spaces 75 4.3 Extension Principle Based on the Triangular Norms 84 4.4 Generalized Extension Principle 92 5 Generating Fuzzy Sets 109 5.1 Families of Sets 110 5.2 Nested Families 112 5.3 Generating Fuzzy Sets from Nested Families 119 5.4 Generating Fuzzy Sets Based on the Expression in the Decomposition Theorem 123 5.4.1 The Ordinary Situation 123 5.4.2 Based on One Function 129 Trim Size: 170mm x 244mm Single Column Tight Wu981527 ftoc.tex V1 - 10/14/2022 2:05pm Page vi [1] [1] [1] [1] vi Contents 5.4.3 Based on Two Functions 140 5.5 Generating Fuzzy Intervals 150 5.6 Uniqueness of Construction 160 6 Fuzzification of Crisp Functions 173 6.1 Fuzzification Using the Extension Principle 173 6.2 Fuzzification Using the Expression in the Decomposition Theorem 176 6.2.1 Nested Family Using 𝛼-Level Sets 177 6.2.2 Nested Family Using Endpoints 181 6.2.3 Non-Nested Family Using Endpoints 184 6.3 The Relationships between EP and DT 187 6.3.1 The Equivalences 187 6.3.2 The Fuzziness 191 6.4 Differentiation of Fuzzy Functions 196 6.4.1 Defined on Open Intervals 196 6.4.2 Fuzzification of Differentiable Functions Using the Extension Principle 197 6.4.3 Fuzzification of Differentiable Functions Using the Expression in the Decomposition Theorem 198 6.5 Integrals of Fuzzy Functions 201 6.5.1 Lebesgue Integrals on a Measurable Set 201 6.5.2 Fuzzy Riemann Integrals Using the Expression in the Decomposition Theorem 203 6.5.3 Fuzzy Riemann Integrals Using the Extension Principle 207 7 Arithmetics of Fuzzy Sets 211 7.1 Arithmetics of Fuzzy Sets in ℝ 211 7.1.1 Arithmetics of Fuzzy Intervals 214 7.1.2 Arithmetics Using EP and DT 220 7.1.2.1 Addition of Fuzzy Intervals 220 7.1.2.2 Difference of Fuzzy Intervals 222 7.1.2.3 Multiplication of Fuzzy Intervals 224 7.2 Arithmetics of Fuzzy Vectors 227 7.2.1 Arithmetics Using the Extension Principle 230 7.2.2 Arithmetics Using the Expression in the Decomposition Theorem 230 7.3 Difference of Vectors of Fuzzy Intervals 235 7.3.1 𝛼-Level Sets of 𝐀̃⊖EP 𝐁̃ 235 7.3.2 𝛼-Level Sets of 𝐀̃ ⊖⋄ DT 𝐁̃ 237 7.3.3 𝛼-Level Sets of 𝐀̃ ⊖⋆ DT 𝐁̃ 239 7.3.4 𝛼-Level Sets of 𝐀̃ ⊖† DT 𝐁̃ 241 7.3.5 The Equivalences and Fuzziness 243 7.4 Addition of Vectors of Fuzzy Intervals 244 7.4.1 𝛼-Level Sets of 𝐀̃⊕EP 𝐁̃ 244 7.4.2 𝛼-Level Sets of 𝐀̃⊕DT 𝐁̃ 246 Trim Size: 170mm x 244mm Single Column Tight Wu981527 ftoc.tex V1 - 10/14/2022 2:05pm Page vii [1] [1] [1] [1] Contents vii 7.5 Arithmetic Operations Using Compatibility and Associativity 249 7.5.1 Compatibility 250 7.5.2 Associativity 255 7.5.3 Computational Procedure 264 7.6 Binary Operations 268 7.6.1 First Type of Binary Operation 269 7.6.2 Second Type of Binary Operation 273 7.6.3 Third Type of Binary Operation 274 7.6.4 Existence and Equivalence 277 7.6.5 Equivalent Arithmetic Operations on Fuzzy Sets in ℝ 282 7.6.6 Equivalent Additions of Fuzzy Sets in ℝm 289 7.7 Hausdorff Differences 294 7.7.1 Fair Hausdorff Difference 294 7.7.2 Composite Hausdorff Difference 299 7.7.3 Complete Composite Hausdorff Difference 304 7.8 Applications and Conclusions 312 7.8.1 Gradual Numbers 312 7.8.2 Fuzzy Linear Systems 313 7.8.3 Summary and Conclusion 315 8 Inner Product of Fuzzy Vectors 317 8.1 The First Type of Inner Product 317 8.1.1 Using the Extension Principle 318 8.1.2 Using the Expression in the Decomposition Theorem 322 8.1.2.1 The Inner Product 𝐀̃ ⊛⋄ DT 𝐁̃ 323 8.1.2.2 The Inner Product 𝐀̃ ⊛⋆ DT 𝐁̃ 325 8.1.2.3 The Inner Product 𝐀̃ ⊛† DT 𝐁̃ 327 8.1.3 The Equivalences and Fuzziness 329 8.2 The Second Type of Inner Product 330 8.2.1 Using the Extension Principle 333 8.2.2 Using the Expression in the Decomposition Theorem 335 8.2.3 Comparison of Fuzziness 338 9 Gradual Elements and Gradual Sets 343 9.1 Gradual Elements and Gradual Sets 343 9.2 Fuzzification Using Gradual Numbers 347 9.3 Elements and Subsets of Fuzzy Intervals 348 9.4 Set Operations Using Gradual Elements 351 9.4.1 Complement Set 351 9.4.2 Intersection and Union 353 9.4.3 Associativity 359 9.4.4 Equivalence with the Conventional Situation 363 9.5 Arithmetics Using Gradual Numbers 364 Trim Size: 170mm x 244mm Single Column Tight Wu981527 ftoc.tex V1 - 10/14/2022 2:05pm Page viii [1] [1] [1] [1] viii Contents 10 Duality in Fuzzy Sets 373 10.1 Lower and Upper Level Sets 373 10.2 Dual Fuzzy Sets 376 10.3 Dual Extension Principle 378 10.4 Dual Arithmetics of Fuzzy Sets 380 10.5 Representation Theorem for Dual-Fuzzified Function 385 Bibliography 389 Mathematical Notations 397 Index 401

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Book SynopsisDeterministic and Stochastic Modeling in Computational Electromagnetics Help protect your network with this important reference work on cyber security Deterministic computational models are those for which all inputs are precisely known, whereas stochastic modeling reflects uncertainty or randomness in one or more of the data inputs. Many problems in computational engineering therefore require both deterministic and stochastic modeling to be used in parallel, allowing for different degrees of confidence and incorporating datasets of different kinds. In particular, non-intrusive stochastic methods can be easily combined with widely used deterministic approaches, enabling this more robust form of data analysis to be applied to a range of computational challenges. Deterministic and Stochastic Modeling in Computational Electromagnetics provides a rare treatment of parallel deterministicstochastic computational modeling and its beneficial applications. Unlike Table of ContentsAbout the Authors xv Preface xvii Part I Some Fundamental Principles in Field Theory 1 1 Least Action Principle in Electromagnetics 3 1.1 Hamilton Principle 4 1.2 Newton's Equation of Motion from Lagrangian 7 1.3 Noether's Theorem and Conservation Laws 8 1.4 Equation of Continuity from Lagrangian 12 1.5 Lorentz Force from Gauge Invariance 16 2 Fundamental Equations of Engineering Electromagnetics 21 2.1 Derivation of Two-Canonical Maxwell's Equation 21 2.2 Derivation of Two-Dynamical Maxwell's Equation 22 2.3 Integral Form of Maxwell's Equations, Continuity Equations, and Lorentz Force 25 2.4 Phasor Form of Maxwell's Equations 27 2.5 Continuity (Interface) Conditions 29 2.6 Poynting Theorem 30 2.7 Electromagnetic Wave Equations 32 2.8 Plane Wave Propagation 35 2.9 Hertz Dipole as a Simple Radiation Source 37 2.10 Wire Antennas of Finite Length 41 3 Variational Methods in Electromagnetics 47 3.1 Analytical Methods 47 3.2 Variational Basis for Numerical Methods 51 4 Outline of Numerical Methods 57 4.1 Variational Basis for Numerical Methods 60 4.2 The Finite Element Method 61 4.3 The Boundary Element Method 77 Part II Deterministic Modeling 87 5 Wire Configurations – Frequency Domain Analysis 89 5.1 Single Wire in the Presence of a Lossy Half-Space 89 5.2 Horizontal Dipole Above a Multi-layered Lossy Half-Space 100 5.3 Wire Array Above a Multilayer 125 5.4 Wires of Arbitrary Shape Radiating Over a Layered Medium 150 5.5 Complex Power of Arbitrarily Shaped Thin Wire Radiating Above a Lossy Half-Space 186 6 Wire Configurations – Time Domain Analysis 207 6.1 Single Wire Above a Lossy Ground 208 6.2 Numerical Solution of Hallen Equation via the Galerkin–Bubnov Indirect Boundary Element Method (GB-IBEM) 222 6.3 Application to Ground-Penetrating Radar 228 6.4 Simplified Calculation of Specific Absorption in Human Tissue 246 6.5 Time Domain Energy Measures 255 6.6 Time Domain Analysis of Multiple Straight Wires above a Half-Space by Means of Various Time Domain Measures 260 7 Bioelectromagnetics – Exposure of Humans in GHz Frequency Range 285 7.1 Assessment of Sab in a Planar Single Layer Tissue 286 7.2 Assessment of Transmitted Power Density in a Single Layer Tissue 295 7.3 Assessment of Sab in a Multilayer Tissue Model 318 7.4 Assessment of Transmitted Power Density in the Planar Multilayer Tissue Model 325 8 Multiphysics Phenomena 339 8.1 Electromagnetic-Thermal Modeling of Human Exposure to HF Radiation 340 8.2 Magnetohydrodynamics (MHD) Models for Plasma Confinement 348 8.3 Modeling of the Schrodinger Equation 370 Part III Stochastic Modeling 385 9 Methods for Stochastic Analysis 387 9.1 Uncertainty Quantification Framework 388 9.2 Stochastic Collocation Method 393 9.3 Sensitivity Analysis 402 10 Stochastic–Deterministic Electromagnetic Dosimetry 407 10.1 Internal Stochastic Dosimetry for a Simple Body Model Exposed to Low-Frequency Field 408 10.2 Internal Stochastic Dosimetry for a Simple Body Model Exposed to Electromagnetic Pulse 413 10.3 Internal Stochastic Dosimetry for a Realistic Three-Compartment Human Head Exposed to High-Frequency Plane Wave 417 10.4 Incident Field Stochastic Dosimetry for Base Station Antenna Radiation 423 11 Stochastic–Deterministic Thermal Dosimetry 433 11.1 Stochastic Sensitivity Analysis of Bioheat Transfer Equation 434 11.2 Stochastic Thermal Dosimetry for Homogeneous Human Brain 437 11.3 Stochastic Thermal Dosimetry for Three-Compartment Human Head 447 11.4 Stochastic Thermal Dosimetry below 6 GHz for 5G Mobile Communication Systems 450 12 Stochastic–Deterministic Modeling in Biomedical Applications of Electromagnetic Fields 459 12.1 Transcranial Magnetic Stimulation 460 12.2 Transcranial Electric Stimulation 466 12.3 Neuron's Action Potential Dynamics 481 12.4 Radiation Efficiency of Implantable Antennas 488 13 Stochastic–Deterministic Modeling of Wire Configurations in Frequency and Time Domain 503 13.1 Ground-Penetrating Radar 503 13.2 Grounding Systems 515 13.3 Air Traffic Control Systems 523 14 A Note on Stochastic Modeling of Plasma Physics Phenomena 535 14.1 Tokamak Current Diffusion Equation 535 References 543 Index 545

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Book SynopsisIdentification of a physical system deals with the problem of identifying its mathematical model using the measured input and output data. As the physical system is generally complex, nonlinear, and its input output data is corrupted noise, there are fundamental theoretical and practical issues that need to be considered.Table of ContentsPreface xv Nomenclature xxi 1 Modeling of Signals and Systems 1 1.1 Introduction 1 1.2 Classification of Signals 2 1.2.1 Deterministic and Random Signals 3 1.2.2 Bounded and Unbounded Signal 3 1.2.3 Energy and Power Signals 3 1.2.4 Causal, Non-causal, and Anti-causal Signals 4 1.2.5 Causal, Non-causal, and Anti-causal Systems 4 1.3 Model of Systems and Signals 5 1.3.1 Time-Domain Model 5 1.3.2 Frequency-Domain Model 8 1.4 Equivalence of Input–Output and State-Space Models 8 1.4.1 State-Space and Transfer Function Model 8 1.4.2 Time-Domain Expression for the Output Response 8 1.4.3 State-Space and the Difference Equation Model 9 1.4.4 Observer Canonical Form 9 1.4.5 Characterization of the Model 10 1.4.6 Stability of (Discrete-Time) Systems 10 1.4.7 Minimum Phase System 11 1.4.8 Pole-Zero Locations and the Output Response 11 1.5 Deterministic Signals 11 1.5.1 Transfer Function Model 12 1.5.2 Difference Equation Model 12 1.5.3 State-Space Model 14 1.5.4 Expression for an Impulse Response 14 1.5.5 Periodic Signal 14 1.5.6 Periodic Impulse Train 15 1.5.7 A Finite Duration Signal 16 1.5.8 Model of a Class of All Signals 17 1.5.9 Examples of Deterministic Signals 18 1.6 Introduction to Random Signals 23 1.6.1 Stationary Random Signal 23 1.6.2 Joint PDF and Statistics of Random Signals 24 1.6.3 Ergodic Process 27 1.7 Model of Random Signals 28 1.7.1 White Noise Process 29 1.7.2 Colored Noise 30 1.7.3 Model of a Random Waveform 30 1.7.4 Classification of the Random Waveform 31 1.7.5 Frequency Response and Pole-Zero Locations 31 1.7.6 Illustrative Examples of Filters 36 1.7.7 Illustrative Examples of Random Signals 36 1.7.8 Pseudo Random Binary Sequence (PRBS) 38 1.8 Model of a System with Disturbance and Measurement Noise 41 1.8.1 Input–Output Model of the System 41 1.8.2 State-Space Model of the System 44 1.8.3 Illustrative Examples in Integrated System Model 47 1.9 Summary 50 References 54 Further Readings 54 2 Characterization of Signals: Correlation and Spectral Density 57 2.1 Introduction 57 2.2 Definitions of Auto- and Cross-Correlation (and Covariance) 58 2.2.1 Properties of Correlation 61 2.2.2 Normalized Correlation and Correlation Coefficient 66 2.3 Spectral Density: Correlation in the Frequency Domain 67 2.3.1 Z-transform of the Correlation Function 69 2.3.2 Expressions for Energy and Power Spectral Densities 71 2.4 Coherence Spectrum 74 2.5 Illustrative Examples in Correlation and Spectral Density 76 2.5.1 Deterministic Signals: Correlation and Spectral Density 76 2.5.2 Random Signals: Correlation and Spectral Density 87 2.6 Input–Output Correlation and Spectral Density 91 2.6.1 Generation of Random Signal from White Noise 92 2.6.2 Identification of Non-Parametric Model of a System 93 2.6.3 Identification of a Parametric Model of a Random Signal 94 2.7 Illustrative Examples: Modeling and Identification 98 2.8 Summary 109 2.9 Appendix 112 References 116 3 Estimation Theory 117 3.1 Overview 117 3.2 Map Relating Measurement and the Parameter 119 3.2.1 Mathematical Model 119 3.2.2 Probabilistic Model 120 3.2.3 Likelihood Function 122 3.3 Properties of Estimators 123 3.3.1 Indirect Approach to Estimation 123 3.3.2 Unbiasedness of the Estimator 124 3.3.3 Variance of the Estimator: Scalar Case 125 3.3.4 Median of the Data Samples 125 3.3.5 Small and Large Sample Properties 126 3.3.6 Large Sample Properties 126 3.4 Cramér–Rao Inequality 127 3.4.1 Scalar Case: and ̂ Scalars while y is a Nx1 Vector 128 3.4.2 Vector Case: is a Mx1 Vector 129 3.4.3 Illustrative Examples: Cramér–Rao Inequality 130 3.4.4 Fisher Information 138 3.5 Maximum Likelihood Estimation 139 3.5.1 Formulation of Maximum Likelihood Estimation 139 3.5.2 Illustrative Examples: Maximum Likelihood Estimation of Mean or Median 141 3.5.3 Illustrative Examples: Maximum Likelihood Estimation of Mean and Variance 148 3.5.4 Properties of Maximum Likelihood Estimator 154 3.6 Summary 154 3.7 Appendix: Cauchy–Schwarz Inequality 157 3.8 Appendix: Cram´er–Rao Lower Bound 157 3.8.1 Scalar Case 158 3.8.2 Vector Case 160 3.9 Appendix: Fisher Information: Cauchy PDF 161 3.10 Appendix: Fisher Information for i.i.d. PDF 161 3.11 Appendix: Projection Operator 162 3.12 Appendix: Fisher Information: Part Gauss-Part Laplace 164 Problem 165 References 165 Further Readings 165 4 Estimation of Random Parameter 167 4.1 Overview 167 4.2 Minimum Mean-Squares Estimator (MMSE): Scalar Case 167 4.2.1 Conditional Mean: Optimal Estimator 168 4.3 MMSE Estimator: Vector Case 169 4.3.1 Covariance of the Estimation Error 171 4.3.2 Conditional Expectation and Its Properties 172 4.4 Expression for Conditional Mean 172 4.4.1 MMSE Estimator: Gaussian Random Variables 173 4.4.2 MMSE Estimator: Unknown is Gaussian and Measurement Non-Gaussian 174 4.4.3 The MMSE Estimator for Gaussian PDF 176 4.4.4 Illustrative Examples 178 4.5 Summary 183 4.6 Appendix: Non-Gaussian Measurement PDF 184 4.6.1 Expression for Conditional Expectation 184 4.6.2 Conditional Expectation for Gaussian x and Non-Gaussian y 185 References 188 Further Readings 188 5 Linear Least-Squares Estimation 189 5.1 Overview 189 5.2 Linear Least-Squares Approach 189 5.2.1 Linear Algebraic Model 190 5.2.2 Least-Squares Method 190 5.2.3 Objective Function 191 5.2.4 Optimal Least-Squares Estimate: Normal Equation 193 5.2.5 Geometric Interpretation of Least-Squares Estimate: Orthogonality Principle 194 5.3 Performance of the Least-Squares Estimator 195 5.3.1 Unbiasedness of the Least-Squares Estimate 195 5.3.2 Covariance of the Estimation Error 197 5.3.3 Properties of the Residual 198 5.3.4 Model and Systemic Errors: Bias and the Variance Errors 201 5.4 Illustrative Examples 205 5.4.1 Non-Zero-Mean Measurement Noise 209 5.5 Cram´er–Rao Lower Bound 209 5.6 Maximum Likelihood Estimation 210 5.6.1 Illustrative Examples 210 5.7 Least-Squares Solution of Under-Determined System 212 5.8 Singular Value Decomposition 213 5.8.1 Illustrative Example: Singular and Eigenvalues of Square Matrices 215 5.8.2 Computation of Least-Squares Estimate Using the SVD 216 5.9 Summary 218 5.10 Appendix: Properties of the Pseudo-Inverse and the Projection Operator 221 5.10.1 Over-Determined System 221 5.10.2 Under-Determined System 222 5.11 Appendix: Positive Definite Matrices 222 5.12 Appendix: Singular Value Decomposition of a Matrix 223 5.12.1 SVD and Eigendecompositions 225 5.12.2 Matrix Norms 226 5.12.3 Least Squares Estimate for Any Arbitrary Data Matrix H 226 5.12.4 Pseudo-Inverse of Any Arbitrary Matrix 228 5.12.5 Bounds on the Residual and the Covariance of the Estimation Error 228 5.13 Appendix: Least-Squares Solution for Under-Determined System 228 5.14 Appendix: Computation of Least-Squares Estimate Using the SVD 229 References 229 Further Readings 230 6 Kalman Filter 231 6.1 Overview 231 6.2 Mathematical Model of the System 233 6.2.1 Model of the Plant 233 6.2.2 Model of the Disturbance and Measurement Noise 233 6.2.3 Integrated Model of the System 234 6.2.4 Expression for the Output of the Integrated System 235 6.2.5 Linear Regression Model 235 6.2.6 Observability 236 6.3 Internal Model Principle 236 6.3.1 Controller Design Using the Internal Model Principle 237 6.3.2 Internal Model (IM) of a Signal 237 6.3.3 Controller Design 238 6.3.4 Illustrative Example: Controller Design 241 6.4 Duality Between Controller and an Estimator Design 244 6.4.1 Estimation Problem 244 6.4.2 Estimator Design 244 6.5 Observer: Estimator for the States of a System 246 6.5.1 Problem Formulation 246 6.5.2 The Internal Model of the Output 246 6.5.3 Illustrative Example: Observer with Internal Model Structure 247 6.6 Kalman Filter: Estimator of the States of a Stochastic System 250 6.6.1 Objectives of the Kalman Filter 251 6.6.2 Necessary Structure of the Kalman Filter 252 6.6.3 Internal Model of a Random Process 252 6.6.4 Illustrative Example: Role of an Internal Model 254 6.6.5 Model of the Kalman Filter 255 6.6.6 Optimal Kalman Filter 256 6.6.7 Optimal Scalar Kalman Filter 256 6.6.8 Optimal Kalman Gain 260 6.6.9 Comparison of the Kalman Filters: Integrated and Plant Models 260 6.6.10 Steady-State Kalman Filter 261 6.6.11 Internal Model and Statistical Approaches 261 6.6.12 Optimal Information Fusion 262 6.6.13 Role of the Ratio of Variances 262 6.6.14 Fusion of Information from the Model and the Measurement 263 6.6.15 Illustrative Example: Fusion of Information 264 6.6.16 Orthogonal Properties of the Kalman Filter 266 6.6.17 Ensemble and Time Averages 266 6.6.18 Illustrative Example: Orthogonality Properties of the Kalman Filter 267 6.7 The Residual of the Kalman Filter with Model Mismatch and Non-Optimal Gain 267 6.7.1 State Estimation Error with Model Mismatch 268 6.7.2 Illustrative Example: Residual with Model Mismatch and Non-Optimal Gain 271 6.8 Summary 274 6.9 Appendix: Estimation Error Covariance and the Kalman Gain 277 6.10 Appendix: The Role of the Ratio of Plant and the Measurement Noise Variances 279 6.11 Appendix: Orthogonal Properties of the Kalman Filter 279 6.11.1 Span of a Matrix 284 6.11.2 Transfer Function Formulae 284 6.12 Appendix: Kalman Filter Residual with Model Mismatch 285 References 287 7 System Identification 289 7.1 Overview 289 7.2 System Model 291 7.2.1 State-Space Model 291 7.2.2 Assumptions 292 7.2.3 Frequency-Domain Model 292 7.2.4 Input Signal for System Identification 293 7.3 Kalman Filter-Based Identification Model Structure 297 7.3.1 Expression for the Kalman Filter Residual 298 7.3.2 Direct Form or Colored Noise Form 300 7.3.3 Illustrative Examples: Process, Predictor, and Innovation Forms 302 7.3.4 Models for System Identification 304 7.3.5 Identification Methods 305 7.4 Least-Squares Method 307 7.4.1 Linear Matrix Model: Batch Processing 308 7.4.2 The Least-Squares Estimate 308 7.4.3 Quality of the Least-Squares Estimate 312 7.4.4 Illustrative Example of the Least-Squares Identification 313 7.4.5 Computation of the Estimates Using Singular Value Decomposition 315 7.4.6 Recursive Least-Squares Identification 316 7.5 High-Order Least-Squares Method 318 7.5.1 Justification for a High-Order Model 318 7.5.2 Derivation of a Reduced-Order Model 323 7.5.3 Formulation of Model Reduction 324 7.5.4 Model Order Selection 324 7.5.5 Illustrative Example of High-Order Least-Squares Method 325 7.5.6 Performance of the High-Order Least-Squares Scheme 326 7.6 The Prediction Error Method 327 7.6.1 Residual Model 327 7.6.2 Objective Function 327 7.6.3 Iterative Prediction Algorithm 328 7.6.4 Family of Prediction Error Algorithms 330 7.7 Comparison of High-Order Least-Squares and the Prediction Error Methods 330 7.7.1 Illustrative Example: LS, High Order LS, and PEM 331 7.8 Subspace Identification Method 334 7.8.1 Identification Model: Predictor Form of the Kalman Filter 334 7.9 Summary 340 7.10 Appendix: Performance of the Least-Squares Approach 347 7.10.1 Correlated Error 347 7.10.2 Uncorrelated Error 347 7.10.3 Correlation of the Error and the Data Matrix 348 7.10.4 Residual Analysis 350 7.11 Appendix: Frequency-Weighted Model Order Reduction 352 7.11.1 Implementation of the Frequency-Weighted Estimator 354 7.11.2 Selection of the Frequencies 354 References 354 8 Closed Loop Identification 357 8.1 Overview 357 8.1.1 Kalman Filter-Based Identification Model 358 8.1.2 Closed-Loop Identification Approaches 358 8.2 Closed-Loop System 359 8.2.1 Two-Stage and Direct Approaches 359 8.3 Model of the Single Input Multi-Output System 360 8.3.1 State- Space Model of the Subsystem 360 8.3.2 State-Space Model of the Overall System 361 8.3.3 Transfer Function Model 361 8.3.4 Illustrative Example: Closed-Loop Sensor Network 362 8.4 Kalman Filter-Based Identification Model 364 8.4.1 State-Space Model of the Kalman Filter 364 8.4.2 Residual Model 365 8.4.3 The Identification Model 366 8.5 Closed-Loop Identification Schemes 366 8.5.1 The High-Order Least-Squares Method 366 8.6 Second Stage of the Two-Stage Identification 372 8.7 Evaluation on a Simulated Closed-Loop Sensor Net 372 8.7.1 The Performance of the Stage I Identification Scheme 372 8.7.2 The Performance of the Stage II Identification Scheme 373 8.8 Summary 374 References 377 9 Fault Diagnosis 379 9.1 Overview 379 9.1.1 Identification for Fault Diagnosis 380 9.1.2 Residual Generation 380 9.1.3 Fault Detection 380 9.1.4 Fault Isolation 381 9.2 Mathematical Model of the System 381 9.2.1 Linear Regression Model: Nominal System 382 9.3 Model of the Kalman Filter 382 9.4 Modeling of Faults 383 9.4.1 Linear Regression Model 383 9.5 Diagnostic Parameters and the Feature Vector 384 9.6 Illustrative Example 386 9.6.1 Mathematical Model 386 9.6.2 Feature Vector and the Influence Vectors 387 9.7 Residual of the Kalman Filter 388 9.7.1 Diagnostic Model 389 9.7.2 Key Properties of the Residual 389 9.7.3 The Role of the Kalman Filter in Fault Diagnosis 389 9.8 Fault Diagnosis 390 9.9 Fault Detection: Bayes Decision Strategy 390 9.9.1 Pattern Classification Problem: Fault Detection 391 9.9.2 Generalized Likelihood Ratio Test 392 9.9.3 Maximum Likelihood Estimate 392 9.9.4 Decision Strategy 394 9.9.5 Other Test Statistics 395 9.10 Evaluation of Detection Strategy on Simulated System 396 9.11 Formulation of Fault Isolation Problem 396 9.11.1 Pattern Classification Problem: Fault Isolation 397 9.11.2 Formulation of the Fault Isolation Scheme 398 9.11.3 Fault Isolation Tasks 399 9.12 Estimation of the Influence Vectors and Additive Fault 399 9.12.1 Parameter-Perturbed Experiment 400 9.12.2 Least-Squares Estimates 401 9.13 Fault Isolation Scheme 401 9.13.1 Sequential Fault Isolation Scheme 402 9.13.2 Isolation of the Fault 403 9.14 Isolation of a Single Fault 403 9.14.1 Fault Discriminant Function 403 9.14.2 Performance of Fault Isolation Scheme 404 9.14.3 Performance Issues and Guidelines 405 9.15 Emulators for Offline Identification 406 9.15.1 Examples of Emulators 407 9.15.2 Emulators for Multiple Input-Multiple-Output System 407 9.15.3 Role of an Emulator 408 9.15.4 Criteria for Selection 409 9.16 Illustrative Example 409 9.16.1 Mathematical Model 409 9.16.2 Selection of Emulators 410 9.16.3 Transfer Function Model 410 9.16.4 Role of the Static Emulators 411 9.16.5 Role of the Dynamic Emulator 412 9.17 Overview of Fault Diagnosis Scheme 414 9.18 Evaluation on a Simulated Example 414 9.18.1 The Kalman Filter 414 9.18.2 The Kalman Filter Residual and Its Auto-correlation 414 9.18.3 Estimation of the Influence Vectors 416 9.18.4 Fault Size Estimation 416 9.18.5 Fault Isolation 417 9.19 Summary 418 9.20 Appendix: Bayesian Multiple Composite Hypotheses Testing Problem 422 9.21 Appendix: Discriminant Function for Fault Isolation 423 9.22 Appendix: Log-Likelihood Ratio for a Sinusoid and a Constant 424 9.22.1 Determination of af, bf , and cf 424 9.22.2 Determination of the Optimal Cost 425 References 426 10 Modeling and Identification of Physical Systems 427 10.1 Overview 427 10.2 Magnetic Levitation System 427 10.2.1 Mathematic Model of a Magnetic Levitation System 427 10.2.2 Linearized Model 429 10.2.3 Discrete-Time Equivalent of Continuous-Time Models 430 10.2.4 Identification Approach 432 10.2.5 Identification of the Magnetic Levitation System 433 10.3 Two-Tank Process Control System 436 10.3.1 Model of the Two-Tank System 436 10.3.2 Identification of the Closed-Loop Two-Tank System 438 10.4 Position Control System 442 10.4.1 Experimental Setup 442 10.4.2 Mathematical Model of the Position Control System 442 10.5 Summary 444 References 446 11 Fault Diagnosis of Physical Systems 447 11.1 Overview 447 11.2 Two-Tank Physical Process Control System 448 11.2.1 Objective 448 11.2.2 Identification of the Physical System 448 11.2.3 Fault Detection 449 11.2.4 Fault Isolation 451 11.3 Position Control System 452 11.3.1 The Objective 452 11.3.2 Identification of the Physical System 452 11.3.3 Detection of Fault 455 11.3.4 Fault Isolation 455 11.3.5 Fault Isolability 455 11.4 Summary 457 References 457 12 Fault Diagnosis of a Sensor Network 459 12.1 Overview 459 12.2 Problem Formulation 461 12.3 Fault Diagnosis Using a Bank of Kalman Filters 461 12.4 Kalman Filter for Pairs of Measurements 462 12.5 Kalman Filter for the Reference Input-Measurement Pair 463 12.6 Kalman Filter Residual: A Model Mismatch Indicator 463 12.6.1 Residual for a Pair of Measurements 463 12.7 Bayes Decision Strategy 464 12.8 Truth Table of Binary Decisions 465 12.9 Illustrative Example 467 12.10 Evaluation on a Physical Process Control System 469 12.11 Fault Detection and Isolation 470 12.11.1 Comparison with Other Approaches 473 12.12 Summary 474 12.13 Appendix 475 12.13.1 Map Relating yi(z) to yj(z) 475 12.13.2 Map Relating r(z) to yj(z) 476 References 477 13 Soft Sensor 479 13.1 Review 479 13.1.1 Benefits of a Soft Sensor 479 13.1.2 Kalman Filter 479 13.1.3 Reliable Identification of the System 480 13.1.4 Robust Controller Design 480 13.1.5 Fault Tolerant System 481 13.2 Mathematical Formulation 481 13.2.1 Transfer Function Model 482 13.2.2 Uncertainty Model 482 13.3 Identification of the System 483 13.3.1 Perturbed Parameter Experiment 484 13.3.2 Least-Squares Estimation 484 13.3.3 Selection of the Model Order 485 13.3.4 Identified Nominal Model 485 13.3.5 Illustrative Example 486 13.4 Model of the Kalman Filter 488 13.4.1 Role of the Kalman Filter 488 13.4.2 Model of the Kalman Filter 489 13.4.3 Augmented Model of the Plant and the Kalman Filter 489 13.5 Robust Controller Design 489 13.5.1 Objective 489 13.5.2 Augmented Model 490 13.5.3 Closed-Loop Performance and Stability 490 13.5.4 Uncertainty Model 491 13.5.5 Mixed-sensitivity Optimization Problem 492 13.5.6 State-Space Model of the Robust Control System 493 13.6 High Performance and Fault Tolerant Control System 494 13.6.1 Residual and Model-mismatch 494 13.6.2 Bayes Decision Strategy 495 13.6.3 High Performance Control System 495 13.6.4 Fault-Tolerant Control System 496 13.7 Evaluation on a Simulated System: Soft Sensor 496 13.7.1 Offline Identification 497 13.7.2 Identified Model of the Plant 497 13.7.3 Mixed-sensitivity Optimization Problem 498 13.7.4 Performance and Robustness 499 13.7.5 Status Monitoring 499 13.8 Evaluation on a Physical Velocity Control System 500 13.9 Conclusions 502 13.10 Summary 503 References 507 Index 509

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Book SynopsisMobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task.Table of ContentsList of Figures xv List of Tables xxiii About the Author xxv Preface xxvii Acknowledgments xxxiii List of Abbreviations xxxv Part I INTRODUCTION 1 Next Generation Wireless Networks 3 1.1 WLAN and Mesh Networks 5 1.2 Ad Hoc Networks 8 1.3 Vehicular Networks 10 1.4 Wireless Sensor Networks 13 1.5 Opportunistic Networks 14 2 Modeling Next Generation Wireless Networks 19 2.1 Radio Channel Models 20 2.2 The Communication Graph 26 2.3 The Energy Model 31 3 Mobility Models for Next Generation Wireless Networks 33 3.1 Motivation 33 3.2 Cellular vs. Next Generation Wireless Network Mobility Models 35 3.3 A Taxonomy of Existing Mobility Models 38 3.4 Mobility Models and Real-World Traces: The CRAWDAD Resource 43 3.5 Basic Definitions 45 Part II “GENERAL-PURPOSE” MOBILITY MODELS 4 Random Walk Models 51 4.1 Discrete Random Walks 52 4.2 Continuous Random Walks 55 4.3 Other Random Walk Models 57 4.4 Theoretical Properties of Random Walk Models 58 5 The Random Waypoint Model 61 5.1 The RWP Model 62 5.2 The Node Spatial Distribution of the RWP Model 64 5.3 The Average Nodal Speed of the RWP Model 69 5.4 Variants of the RWP Model 73 6 Group Mobility and Other Synthetic Mobility Models 75 6.1 The RPGM Model 76 6.2 Other Synthetic Mobility Models 83 7 Random Trip Models 89 7.1 The Class of Random Trip Models 89 7.2 Stationarity of Random Trip Models 93 7.3 Examples of Random Trip Models 94 Part III MOBILITY MODELS FOR WLAN AND MESH NETWORKS 8 WLAN and Mesh Networks 101 8.1 WLAN and Mesh Networks: State of the Art 101 8.2 WLAN and Mesh Networks: User Scenarios 107 8.3 WLAN and Mesh Networks: Perspectives 109 8.4 Further Reading 111 9 Real-World WLAN Mobility 113 9.1 Real-World WLAN Traces 113 9.2 Features of WLAN Mobility 116 10 WLAN Mobility Models 121 10.1 The LH Mobility Model 122 10.2 The KKK Mobility Model 129 10.3 Final Considerations and Further Reading 137 Part IV MOBILITY MODELS FOR VEHICULAR NETWORKS 11 Vehicular Networks 141 11.1 Vehicular Networks: State of the Art 141 11.2 Vehicular Networks: User Scenarios 146 11.3 Vehicular Networks: Perspectives 150 11.4 Further Reading 151 12 Vehicular Networks: Macroscopic and Microscopic Mobility Models 153 12.1 Vehicular Mobility Models: The Macroscopic View 154 12.2 Vehicular Mobility Models: The Microscopic View 156 12.3 Further Reading 157 13 Microscopic Vehicular Mobility Models 159 13.1 Simple Microscopic Mobility Models 159 13.2 The SUMO Mobility Model 164 13.3 Integrating Vehicular Mobility and Wireless Network Simulation 168 Part V MOBILITY MODELS FOR WIRELESS SENSOR NETWORKS 14 Wireless Sensor Networks 175 14.1 Wireless Sensor Networks: State of the Art 175 14.2 Wireless Sensor Networks: User Scenarios 180 14.3 WSNs: Perspectives 183 14.4 Further Reading 184 15 Wireless Sensor Networks: Passive Mobility Models 185 15.1 Passive Mobility in WSNs 186 15.2 Mobility Models for Wildlife Tracking Applications 187 15.3 Modeling Movement Caused by External Forces 191 16 Wireless Sensor Networks: Active Mobility Models 197 16.1 Active Mobility of Sensor Nodes 198 16.2 Active Mobility of Sink Nodes 208 Part VI MOBILITY MODELS FOR OPPORTUNISTIC NETWORKS 17 Opportunistic Networks 217 17.1 Opportunistic Networks: State of the Art 217 17.2 Opportunistic Networks: User Scenarios 219 17.3 Opportunistic Networks: Perspectives 222 17.4 Further Reading 223 18 Routing in Opportunistic Networks 225 18.1 Mobility-Assisted Routing in Opportunistic Networks 225 18.2 Opportunistic Network Mobility Metrics 231 19 Mobile Social Network Analysis 237 19.1 The Social Network Graph 238 19.2 Centrality and Clustering Metrics 239 19.3 Characterizations of Human Mobility 244 19.4 Further Reading 250 20 Social-Based Mobility Models 251 20.1 The Weighted Random Waypoint Mobility Model 252 20.2 The Time-Variant Community Mobility Model 254 20.3 The Community-Based Mobility Model 256 20.4 The SWIM Mobility Model 259 20.5 The Self-Similar Least Action Walk Model 264 20.6 The Home-MEG Model 267 20.7 Further Reading 270 Part VII CASE STUDIES 21 Random Waypoint Model and Wireless Network Simulation 275 21.1 RWP Model and Simulation Accuracy 276 21.2 Removing the Border Effect 278 21.3 Removing Speed Decay 285 21.4 The RWP Model and “Perfect Simulation” 287 22 Mobility Modeling and Opportunistic Network Performance Analysis 293 22.1 Unicast in Opportunistic Networks 293 22.2 Broadcast in Opportunistic Networks 299 Appendix A Elements of Probability Theory 309 A.1 Basic Notions of Probability Theory 309 A.2 Probability Distributions 313 A.3 Markov Chains 317 Appendix B Elements of Graph Theory, Asymptotic Notation, and Miscellaneous Notions 323 B.1 Asymptotic Notation 323 B.2 Elements of Graph Theory 326 B.3 Miscellaneous Notions 330 References 333 Index 335

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Book SynopsisWith the explosive growth in PV (photovoltaic) installations globally, the sector continues to benefit from important improvements in manufacturing technology and the increasing efficiency of solar cells, this timely handbook brings together all the latest design, layout and construction methods for entire PV plants in a single volume.Trade ReviewReview copy sent 29/02/12: Book News Review copies sent on 2.2.12 to: ENGINEERING STRUCTURES RENEWABLE ENERGY PHOTOVOLTAICS BULLETIN SOLAR ENERGY JOURNAL OF POWER SOURCES ENERGY RESEARCH REAL POWER SOLAR WIND TECHNOLOGY MODERN POWER SYSTEMS ENERGY AND POWER RISK MANAGEMENT NEW POWERTable of ContentsForeword xiii Preface xv About the Author xvii Acknowledgements xix Note on the Examples and Costs xxi List of Symbols xxiii 1 Introduction 1 1.1 Photovoltaics – What’s It All About? 1 1.2 Overview of This Book 1 1.3 A Brief Glossary of Key PV Terms 10 1.4 Recommended Guide Values for Estimating PV System Potential 14 1.5 Examples 24 1.6 Bibliography 25 2 Key Properties of Solar Radiation 27 2.1 Sun and Earth 27 2.2 Extraterrestrial Radiation 31 2.3 Radiation on the Horizontal Plane of the Earth’s Surface 32 2.4 Simple Method for Calculating Solar Radiation on Inclined Surfaces 39 2.5 Radiation Calculation on Inclined Planes with Three-Component Model 49 2.6 Approximate Annual Energy Yield for Grid-Connected PV Systems 68 2.7 Composition of Solar Radiation 71 2.8 Solar Radiation Measurement 71 2.9 Bibliography 76 3 Solar Cells: Their Design Engineering and Operating Principles 79 3.1 The Internal Photoelectric Effect in Semiconductors 79 3.2 A Brief Account of Semiconductor Theory 81 3.3 The Solar Cell: A Specialized Semiconductor Diode With a Large Barrier Layer that is Exposed to Light 86 3.4 Solar Cell Efficiency 94 3.5 The Most Important Types of Solar Cells and the Attendant Manufacturing Methods 108 3.6 Bifacial Solar Cells 122 3.7 Examples 122 3.8 Bibliography 124 4 Solar Modules and Solar Generators 127 4.1 Solar Modules 127 4.2 Potential Solar Cell Wiring Problems 138 4.3 Interconnection of Solar Modules and Solar Generators 149 4.4 Solar Generator Power Loss Resulting from Partial Shading and Mismatch Loss 160 4.5 Solar Generator Structure 166 4.6 Examples 217 4.7 Bibliography 221 5 PV Energy Systems 223 5.1 Stand-alone PV Systems 223 5.2 Grid-Connected Systems 262 5.3 Bibliography 389 6 Protecting PV Installations Against Lightning 395 6.1 Probability of Direct Lightning Strikes 395 6.2 Lightning Strikes: Guide Value; Main Effects 398 6.3 Basic Principles of Lightning Protection 400 6.4 Shunting Lightning Current to a Series of Down-conductors 402 6.5 Potential Increases; Equipotential Bonding 404 6.6 Lightning-Current-Induced Voltages and Current 408 6.7 PV Installation Lightning Protection Experiments 432 6.8 Optimal Sizing of PV Installation Lightning Protection Devices 459 6.9 Recommendations for PV Installation Lightning Protection 470 6.1 Recap and Conclusions 484 6.11 Bibliography 485 7 Standardized Representation of Energy and Power of PV Systems 487 7.1 Introduction 487 7.2 Standardized Yield, Losses and Performance Ratio 487 7.3 Normalized Diagrams for Yields and Losses 491 7.4 Normalized PV Installation Power Output 495 7.5 Anomaly Detection Using Various Types of Diagrams 502 7.6 Recap and Conclusions 506 7.7 Bibliography 506 8 PV Installation Sizing 507 8.1 Principal of and Baseline Values for Yield Calculations 507 8.2 Energy Yield Determination for Grid-Connected Systems 523 8.3 Sizing PV Installations that Integrate a Battery Pack 533 8.4 Insolation Calculation Freeware 549 8.5 Simulation Software 550 8.6 Bibliography 9 The Economics of Solar Power 551 9.1 How Much Does Solar Energy Cost? 553 9.2 Grey Energy; Energy Payback Time; Yield Factor 562 9.3 Bibliography 566 10 Performance Characteristics of Selected PV Installations 569 10.1 Energy Yield Data and Other Aspects of Selected PV Installations 569 10.2 Long Term Comparison of Four Swiss PV Installations 614 10.3 Long Term Energy Yield of the Burgdorf Installation 617 10.4 Mean PV Installation Energy Yield in Germany 619 10.5 Bibliography 620 11 In Conclusion… 623 Annex A: Calculation Tables and Insolation Data 633 A1 Insolation Calculation Tables 633 A2 Aggregate Monthly Horizontal Global Irradiance 634 A3 Global Insolation for Various Reference Locations 634 A4 RB Factors for Insolation Calculations Using the Three-Component Model 648 A5 Shading Diagrams for Various Latitudes 673 A6 Energy Yield Calculation Tables 676 A7 kT and kG Figures for Energy Yield Calculations 681 A8 Insolation and Energy Yield Calculation Maps 683 A8.1 Specimen polar shading diagram Appendix B: Links; Books; Acronyms; etc. 691 B1 Links to PV Web Sites 691 B2 Books on Photovoltaic and Related Areas 693 B3 Acronyms 695 B4 Prefixes for Decimal Fractions and Metric Multiples 696 B5 Conversion Factors 696 B6 Key Physical Constants 696 Index 697

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Book SynopsisThis book addresses a broad range of topics on antennas for space applications. First, it introduces the fundamental methodologies of space antenna design, modelling and analysis as well as the state-of-the-art and anticipated future technological developments. Each of the topics discussed are specialized and contextualized to the space sector.Table of ContentsPreface xvii Acknowledgments xix Acronyms xxi Contributors xxv 1 Antenna Basics 1Luigi Boccia and Olav Breinbjerg 1.1 Introduction 1 1.2 Antenna Performance Parameters 2 1.2.1 Reflection Coefficient and Voltage Standing Wave Ratio 2 1.2.2 Antenna Impedance 3 1.2.3 Radiation Pattern and Coverage 4 1.2.4 Polarization 6 1.2.5 Directivity 7 1.2.6 Gain and Realized Gain 8 1.2.7 Equivalent Isotropically Radiated Power 8 1.2.8 Effective Area 9 1.2.9 Phase Center 9 1.2.10 Bandwidth 9 1.2.11 Antenna Noise Temperature 9 1.3 Basic Antenna Elements 10 1.3.1 Wire Antennas 10 1.3.2 Horn Antennas 10 1.3.3 Reflectors 15 1.3.4 Helical Antennas 17 1.3.5 Printed Antennas 19 1.4 Arrays 26 1.4.1 Array Configurations 28 1.5 Basic Effects of Antennas in the Space Environment 30 1.5.1 Multipaction 30 1.5.2 Passive Inter-modulation 31 1.5.3 Outgassing 31 References 32 2 Space Antenna Modeling 36Jian Feng Zhang, Xue Wei Ping, Wen Ming Yu, Xiao Yang Zhou, and Tie Jun Cui 2.1 Introduction 36 2.1.1 Maxwell’s Equations 37 2.1.2 CEM 37 2.2 Methods of Antenna Modeling 39 2.2.1 Basic Theory 39 2.2.2 Method of Moments 40 2.2.3 FEM 45 2.2.4 FDTD Method 49 2.3 Fast Algorithms for Large Space Antenna Modeling 54 2.3.1 Introduction 54 2.3.2 MLFMA 54 2.3.3 Hierarchical Basis for the FEM 62 2.4 Case Studies: Effects of the Satellite Body on the Radiation Patterns of Antennas 68 2.5 Summary 73 Acknowledgments 73 References 73 3 System Architectures of Satellite Communication, Radar, Navigation and Remote Sensing 76Michael A. Thorburn 3.1 Introduction 76 3.2 Elements of Satellite System Architecture 76 3.3 Satellite Missions 77 3.4 Communications Satellites 77 3.4.1 Fixed Satellite Services 77 3.4.2 Broadcast Satellite Services (Direct Broadcast Services) 78 3.4.3 Digital Audio Radio Services 78 3.4.4 Direct to Home Broadband Services 78 3.4.5 Mobile Communications Services 78 3.5 Radar Satellites 79 3.6 Navigational Satellites 79 3.7 Remote Sensing Satellites 80 3.8 Architecture of Satellite Command and Control 80 3.9 The Communications Payload Transponder 80 3.9.1 Bent-Pipe Transponders 81 3.9.2 Digital Transponders 81 3.9.3 Regenerative Repeater 81 3.10 Satellite Functional Requirements 81 3.10.1 Key Performance Concepts: Coverage, Frequency Allocations 82 3.10.2 Architecture of the Communications Payload 82 3.10.3 Satellite Communications System Performance Requirements 83 3.11 The Satellite Link Equation 83 3.12 The Microwave Transmitter Block 84 3.12.1 Intercept Point 85 3.12.2 Output Backoff 86 3.12.3 The Transmit Antenna and EIRP 87 3.13 Rx Front-End Block 88 3.13.1 Noise Figure and Noise Temperature 88 3.14 Received Power in the Communications System’s RF Link 90 3.14.1 The Angular Dependencies of the Uplink and Downlink 91 3.15 Additional Losses in the Satellite and Antenna 91 3.15.1 Additional Losses due to Propagation Effects and the Atmosphere 91 3.15.2 Ionospheric Effects – Scintillation and Polarization Rotation 93 3.16 Thermal Noise and the Antenna Noise Temperature 93 3.16.1 The Interface between the Antenna and the Communications System 93 3.16.2 The Uplink Signal to Noise 94 3.17 The SNR Equation and Minimum Detectable Signal 94 3.18 Power Flux Density, Saturation Flux Density and Dynamic Range 95 3.18.1 Important Relationship between PFD and Gain State of the Satellite Transponder 95 3.19 Full-Duplex Operation and Passive Intermodulation 96 3.20 Gain and Gain Variation 96 3.21 Pointing Error 97 3.22 Remaining Elements of Satellite System Architecture 98 3.23 Orbits and Orbital Considerations 98 3.24 Spacecraft Introduction 100 3.25 Spacecraft Budgets (Mass, Power, Thermal) 101 3.25.1 Satellite Mass 101 3.25.2 Satellite Power 101 3.25.3 Satellite Thermal Dissipation 101 3.26 Orbital Mission Life and Launch Vehicle Considerations 102 3.27 Environment Management (Thermal, Radiation) 102 3.28 Spacecraft Structure (Acoustic/Dynamic) 103 3.29 Satellite Positioning (Station Keeping) 103 3.30 Satellite Positioning (Attitude Control) 104 3.31 Power Subsystem 104 3.32 Tracking, Telemetry, Command and Monitoring 105 References 105 4 Space Environment and Materials 106J. Santiago-Prowald and L. Salghetti Drioli 4.1 Introduction 106 4.2 The Space Environment of Antennas 106 4.2.1 The Radiation Environment 107 4.2.2 The Plasma Environment 109 4.2.3 The Neutral Environment 110 4.2.4 Space Environment for Typical Spacecraft Orbits 111 4.2.5 Thermal Environment 111 4.2.6 Launch Environment 113 4.3 Selection of Materials in Relation to Their Electromagnetic Properties 117 4.3.1 RF Transparent Materials and Their Use 117 4.3.2 RF Conducting Materials and Their Use 117 4.3.3 Material Selection Golden Rules for PIM Control 118 4.4 Space Materials and Manufacturing Processes 118 4.4.1 Metals and Their Alloys 118 4.4.2 Polymer Matrix Composites 121 4.4.3 Ceramics and Ceramic Matrix Composites 125 4.5 Characterization of Mechanical and Thermal Behaviour 127 4.5.1 Thermal Vacuum Environment and Outgassing Screening 127 4.5.2 Fundamental Characterization Tests of Polymers and Composites 128 4.5.3 Characterization of Mechanical Properties 130 4.5.4 Thermal and Thermoelastic Characterization 131 Acknowledgements 131 References 131 5 Mechanical and Thermal Design of Space Antennas 133J. Santiago-Prowald and Heiko Ritter 5.1 Introduction: The Mechanical–Thermal–Electrical Triangle 133 5.1.1 Antenna Product 134 5.1.2 Configuration, Materials and Processes 135 5.1.3 Review of Requirements and Their Verification 136 5.2 Design of Antenna Structures 136 5.2.1 Typical Design Solutions for Reflectors 136 5.2.2 Structural Description of the Sandwich Plate Architecture 143 5.2.3 Thermal Description of the Sandwich Plate Architecture 143 5.2.4 Electrical Description of the Sandwich Plate Architecture in Relation to Thermo-mechanical Design 144 5.3 Structural Modelling and Analysis 144 5.3.1 First-Order Plate Theory 145 5.3.2 Higher Order Plate Theories 148 5.3.3 Classical Laminated Plate Theory 148 5.3.4 Homogeneous Isotropic Plate Versus Symmetric Sandwich Plate 149 5.3.5 Skins Made of Composite Material 150 5.3.6 Honeycomb Core Characteristics 152 5.3.7 Failure Modes of Sandwich Plates 152 5.3.8 Mass Optimization of Sandwich Plate Architecture for Antennas 154 5.3.9 Finite Element Analysis 156 5.3.10 Acoustic Loads on Antennas 159 5.4 Thermal and Thermoelastic Analysis 166 5.4.1 The Thermal Environment of Space Antennas 166 5.4.2 Transverse Thermal Conductance Model of the Sandwich Plate 167 5.4.3 Thermal Balance of the Flat Sandwich Plate 168 5.4.4 Thermal Distortions of a Flat Plate in Space 169 5.4.5 Thermoelastic Stability of an Offset Parabolic Reflector 171 5.4.6 Thermal Analysis Tools 172 5.4.7 Thermal Analysis Cases 173 5.4.8 Thermal Model Uncertainty and Margins 173 5.5 Thermal Control Strategies 173 5.5.1 Requirements and Principal Design Choices 173 5.5.2 Thermal Control Components 174 5.5.3 Thermal Design Examples 176 Acknowledgements 177 References 178 6 Testing of Antennas for Space 179Jerzy Lemanczyk, Hans Juergen Steiner, and Quiterio Garcia 6.1 Introduction 179 6.2 Testing as a Development and Verification Tool 180 6.2.1 Engineering for Test 180 6.2.2 Model Philosophy and Definitions 182 6.2.3 Electrical Model Correlation 190 6.2.4 Thermal Testing and Model Correlation 195 6.3 Antenna Testing Facilities 203 6.3.1 Far-Field Antenna Test Ranges 203 6.3.2 Compact Antenna Test Ranges 203 6.3.3 Near-Field Measurements and Facilities 212 6.3.4 Environmental Test Facilities and Mechanical Testing 220 6.3.5 PIM Testing 224 6.4 Case Study: SMOS 226 6.4.1 The SMOS MIRAS Instrument 227 6.4.2 SMOS Model Philosophy 231 6.4.3 Antenna Pattern Test Campaign 238 References 248 7 Historical Overview of the Development of Space Antennas 250Antoine G. Roederer 7.1 Introduction 250 7.2 The Early Days 252 7.2.1 Wire and Slot Antennas on Simple Satellite Bodies 252 7.2.2 Antenna Computer Modelling Takes Off 254 7.2.3 Existing/Classical Antenna Designs Adapted for Space 259 7.3 Larger Reflectors with Complex Feeding Systems 262 7.3.1 Introduction 262 7.3.2 Multi-frequency Antennas 263 7.3.3 Large Unfurlable Antennas 271 7.3.4 Solid Surface Deployable Reflector Antennas 279 7.3.5 Polarization-Sensitive and Shaped Reflectors 282 7.3.6 Multi-feed Antennas 285 7.4 Array Antennas 297 7.4.1 Conformal Arrays on Spin-Stabilized Satellites 297 7.4.2 Arrays for Remote Sensing 298 7.4.3 Arrays for Telecommunications 302 7.5 Conclusions 306 Acknowledgements 307 References 307 8 Deployable Mesh Reflector Antennas for Space Applications: RF Characterizations 314Paolo Focardi, Paula R. Brown, and Yahya Rahmat-Samii 8.1 Introduction 314 8.2 History of Deployable Mesh Reflectors 315 8.3 Design Considerations Specific to Mesh Reflectors 320 8.4 The SMAP Mission – A Representative Case Study 320 8.4.1 Mission Overview 320 8.4.2 Key Antenna Design Drivers and Constraints 322 8.4.3 RF Performance Determination of Reflector Surface Materials 327 8.4.4 RF Modeling of the Antenna Radiation Pattern 329 8.4.5 Feed Assembly Design 338 8.4.6 Performance Verification 340 8.5 Conclusion 341 Acknowledgments 341 References 341 9 Microstrip Array Technologies for Space Applications 344Antonio Montesano, Luis F. de la Fuente, Fernando Monjas, Vicente GarcÍa, Luis E. Cuesta, Jennifer Campuzano, Ana Trastoy, Miguel Bustamante, Francisco Casares, Eduardo Alonso, David Álvarez, Silvia Arenas, José Luis Serrano, and Margarita Naranjo 9.1 Introduction 344 9.2 Basics of Array Antennas 345 9.2.1 Functional (Driving) Requirements and Array Design Solutions 345 9.2.2 Materials for Passive Arrays Versus Environmental and Design Requirements 347 9.2.3 Array Optimization Methods and Criteria 349 9.3 Passive Arrays 350 9.3.1 Radiating Panels for SAR Antennas 350 9.3.2 Navigation Antennas 354 9.3.3 Passive Antennas for Deep Space 361 9.4 Active Arrays 363 9.4.1 Key Active Elements in Active Antennas: Amplifiers 363 9.4.2 Active Hybrids 366 9.4.3 The Thermal Dissipation Design Solution 367 9.4.4 Active Array Control 369 9.4.5 Active Arrays for Communications and Data Transmission 370 9.5 Summary 383 Acknowledgements 383 References 384 10 Printed Reflectarray Antennas for Space Applications 385Jose A. Encinar 10.1 Introduction 385 10.2 Principle of Operation and Reflectarray Element Performance 388 10.3 Analysis and Design Techniques 391 10.3.1 Analysis and Design of Reflectarray Elements 391 10.3.2 Design and Analysis of Reflectarray Antennas 393 10.3.3 Broadband Techniques 396 10.4 Reflectarray Antennas for Telecommunication and Broadcasting Satellites 400 10.4.1 Contoured-Beam Reflectarrays 400 10.4.2 Dual-Coverage Transmit Antenna 402 10.4.3 Transmit–Receive Antenna for Coverage of South America 405 10.5 Recent and Future Developments for Space Applications 414 10.5.1 Large-Aperture Reflectarrays 414 10.5.2 Inflatable Reflectarrays 415 10.5.3 High-Gain Antennas for Deep Space Communications 416 10.5.4 Multibeam Reflectarrays 418 10.5.5 Dual-Reflector Configurations 420 10.5.6 Reconfigurable and Steerable Beam Reflectarrays 424 10.5.7 Conclusions and Future Developments 428 Acknowledgments 428 References 429 11 Emerging Antenna Technologies for Space Applications 435Safieddin Safavi-Naeini and Mohammad Fakharzadeh 11.1 Introduction 435 11.2 On-Chip/In-Package Antennas for Emerging Millimeter-Wave Systems 436 11.2.1 Recent Advances in On-Chip Antenna Technology 436 11.2.2 Silicon IC Substrate Limitations for On-Chip Antennas 437 11.2.3 On-Chip Antenna on Integrated Passive Silicon Technology 439 11.3 Integrated Planar Waveguide Technologies 441 11.4 Microwave/mmW MEMS-Based Circuit Technologies for Antenna Applications 445 11.4.1 RF/Microwave MEMS-Based Phase Shifter 447 11.4.2 Reflective-Type Phase Shifters for mmW Beam-Forming Applications 447 11.5 Emerging THz Antenna Systems and Integrated Structures 448 11.5.1 THz Photonics Techniques: THz Generation Using Photo-mixing Antennas 451 11.5.2 THz Generation Using a Photo-mixing Antenna Array 453 11.6 Case Study: Low-Cost/Complexity Antenna Technologies for Land-Mobile Satellite Communications 454 11.6.1 System-Level Requirements 454 11.6.2 Reconfigurable Very Low-Profile Antenna Array Technologies 454 11.6.3 Beam Steering Techniques 455 11.6.4 Robust Zero-Knowledge Beam Control Algorithm 457 11.6.5 A Ku-band Low-Profile, Low-Cost Array System for Vehicular Communication 458 11.7 Conclusions 462 References 462 12 Antennas for Satellite Communications 466Eric Amyotte and LuÍs Martins Camelo 12.1 Introduction and Design Requirements 466 12.1.1 Link Budget Considerations 467 12.1.2 Types of Satellite Communications Antennas 469 12.1.3 Materials 469 12.1.4 The Space Environment and Its Design Implications 470 12.1.5 Designing for Commercial Applications 470 12.2 UHF Satellite Communications Antennas 471 12.2.1 Typical Requirements and Solutions 471 12.2.2 Single-Element Design 472 12.2.3 Array Design 473 12.2.4 Multipactor Threshold 473 12.3 L/S-band Mobile Satellite Communications Antennas 474 12.3.1 Introduction 474 12.3.2 The Need for Large Unfurlable Reflectors 474 12.3.3 Beam Forming 475 12.3.4 Hybrid Matrix Power Amplification 476 12.3.5 Feed Array Element Design 478 12.3.6 Diplexers 478 12.3.7 Range Measurements 479 12.4 C-, Ku- and Ka-band FSS/BSS Antennas 479 12.4.1 Typical Requirements and Solutions 479 12.4.2 The Shaped-Reflector Technology 480 12.4.3 Power Handling 481 12.4.4 Antenna Structures and Reflectors 481 12.4.5 Reflector Antenna Geometries 482 12.4.6 Feed Chains 491 12.5 Multibeam Broadband Satellite Communications Antennas 496 12.5.1 Typical Requirements and Solutions 496 12.5.2 SFB Array-Fed Reflector Antennas 497 12.5.3 FAFR Antennas 500 12.5.4 DRA Antennas 503 12.5.5 RF Sensing and Tracking 503 12.6 Antennas for Non-geostationary Constellations 504 12.6.1 Typical Requirements and Solutions 504 12.6.2 Global Beam Ground Links 505 12.6.3 High-Gain Ground Links 505 12.6.4 Intersatellite Links or Cross-links 506 12.6.5 Feeder Links 507 Acknowledgments 508 References 508 13 SAR Antennas 511Pasquale Capece and Andrea Torre 13.1 Introduction to Spaceborne SAR Systems 511 13.1.1 General Presentation of SAR Systems 511 13.1.2 Azimuth Resolution in Conventional Radar and in SAR 512 13.1.3 Antenna Requirements Versus Performance Parameters 514 13.2 Challenges of Antenna Design for SAR 518 13.2.1 Reflector Antennas 518 13.2.2 Active Antennas and Subsystems 519 13.3 A Review of the Development of Antennas for Spaceborne SAR 534 13.3.1 TecSAR 534 13.3.2 SAR- Lupe 535 13.3.3 ASAR (EnviSat) 535 13.3.4 Radarsat 1 535 13.3.5 Radarsat 2 535 13.3.6 Palsar (ALOS) 535 13.3.7 TerraSAR-X 536 13.3.8 COSMO (SkyMed) 536 13.4 Case Studies of Antennas for Spaceborne SAR 539 13.4.1 Instrument Design 539 13.4.2 SAR Antenna 540 13.5 Ongoing Developments in SAR Antennas 544 13.5.1 Sentinel 1 544 13.5.2 Saocom Mission 544 13.5.3 ALOS 2 545 13.5.4 COSMO Second Generation 545 13.6 Acknowledgments 546 References 546 14 Antennas for Global Navigation Satellite System Receivers 548Chi-Chih Chen, Steven (Shichang) Gao, and Moazam Maqsood 14.1 Introduction 548 14.2 RF Requirements of GNSS Receiving Antenna 551 14.2.1 General RF Requirements 551 14.2.2 Advanced Requirements for Enhanced Position Accuracy and Multipath Signal Suppression 556 14.3 Design Challenges and Solutions for GNSS Antennas 561 14.3.1 Wide Frequency Coverage 562 14.3.2 Antenna Delay Variation with Frequency and Angle 562 14.3.3 Antenna Size Reduction 567 14.3.4 Antenna Platform Scattering Effect 568 14.4 Common and Novel GNSS Antennas 572 14.4.1 Single-Element Antenna 572 14.4.2 Multi-element Antenna Array 580 14.5 Spaceborne GNSS Antennas 582 14.5.1 Requirements for Antennas On Board Spaceborne GNSS Receivers 582 14.5.2 A Review of Antennas Developed for Spaceborne GNSS Receivers 584 14.6 Case Study: Dual-Band Microstrip Patch Antenna for Spacecraft Precise Orbit Determination Applications 586 14.6.1 Antenna Development 586 14.6.2 Results and Discussions 588 14.7 Summary 591 References 592 15 Antennas for Small Satellites 596Steven (Shichang) Gao, Keith Clark, Jan Zackrisson, Kevin Maynard, Luigi Boccia, and Jiadong Xu 15.1 Introduction to Small Satellites 596 15.1.1 Small Satellites and Their Classification 596 15.1.2 Microsatellites and Constellations of Small Satellites 597 15.1.3 Cube Satellites 598 15.1.4 Formation Flying of Multiple Small Satellites 599 15.2 The Challenges of Designing Antennas for Small Satellites 600 15.2.1 Choice of Operating Frequencies 600 15.2.2 Small Ground Planes Compared with the Operational Wavelength 601 15.2.3 Coupling between Antennas and Structural Elements 601 15.2.4 Antenna Pattern 602 15.2.5 Orbital Height 602 15.2.6 Development Cost 602 15.2.7 Production Costs 602 15.2.8 Testing Costs 602 15.2.9 Deployment Systems 603 15.2.10 Volume 603 15.2.11 Mass 603 15.2.12 Shock and Vibration Loads 603 15.2.13 Material Degradation 603 15.2.14 Atomic Oxygen 603 15.2.15 Material Outgassing 604 15.2.16 Creep 604 15.2.17 Material Charging 604 15.2.18 The Interaction between Satellite Antennas and Structure 604 15.3 Review of Antenna Development for Small Satellites 606 15.3.1 Antennas for Telemetry, Tracking and Command (TT&C) 606 15.3.2 Antennas for High-Rate Data Downlink 609 15.3.3 Antennas for Global Navigation Satellite System (GNSS) Receivers and Reflectometry 615 15.3.4 Antennas for Intersatellite Links 618 15.3.5 Other Antennas 619 15.4 Case Studies 621 15.4.1 Case Study 1: Antenna Pointing Mechanism and Horn Antenna 621 15.4.2 Case Study 2: X-band Downlink Helix Antenna 623 15.5 Conclusions 627 References 628 16 Space Antennas for Radio Astronomy 629Paul F. Goldsmith 16.1 Introduction 629 16.2 Overview of Radio Astronomy and the Role of Space Antennas 629 16.3 Space Antennas for Cosmic Microwave Background Studies 631 16.3.1 The Microwave Background 631 16.3.2 Soviet Space Observations of the CMB 632 16.3.3 The Cosmic Background Explorer (COBE) Satellite 633 16.3.4 The Wilkinson Microwave Anisotropy Probe (WMAP) 635 16.3.5 The Planck Mission 637 16.4 Space Radio Observatories for Submillimeter/Far-Infrared Astronomy 641 16.4.1 Overview of Submillimeter/Far-Infrared Astronomy 641 16.4.2 The Submillimeter Wave Astronomy Satellite 643 16.4.3 The Odin Orbital Observatory 646 16.4.4 The Herschel Space Observatory 648 16.4.5 The Future: Millimetron, CALISTO, and Beyond 650 16.5 Low-Frequency Radio Astronomy 652 16.5.1 Overview of Low-Frequency Radio Astronomy 652 16.5.2 Early Low-Frequency Radio Space Missions 653 16.5.3 The Future 655 16.6 Space VLBI 655 16.6.1 Overview of Space VLBI 655 16.6.2 HALCA 656 16.6.3 RadioAstron 658 16.7 Summary 658 Acknowledgments 660 References 660 17 Antennas for Deep Space Applications 664Paula R. Brown, Richard E. Hodges, and Jacqueline C. Chen 17.1 Introduction 664 17.2 Telecommunications Antennas 665 17.3 Case Study I – Mars Science Laboratory 666 17.3.1 MSL Mission Description 666 17.3.2 MSL X-band Antennas 668 17.3.3 MSL UHF Antennas 676 17.3.4 MSL Terminal Descent Sensor (Landing Radar) 680 17.4 Case Study II – Juno 681 17.4.1 Juno Mission Description 681 17.4.2 Telecom Antennas 682 17.4.3 Juno Microwave Radiometer Antennas 684 Acknowledgments 692 References 693 18 Space Antenna Challenges for Future Missions, Key Techniques and Technologies 695Cyril Mangenot and William A. Imbriale 18.1 Overview of Chapter Contents 695 18.2 General Introduction 696 18.3 General Evolution of Space Antenna Needs and Requirements 697 18.4 Develop Large-Aperture Antennas 699 18.4.1 Problem Area and Challenges 699 18.4.2 Present and Expected Future Space Missions 700 18.4.3 Promising Antenna Concepts and Technologies 702 18.5 Increase Telecommunication Satellite Throughput 707 18.5.1 Problem Area and Challenges 707 18.5.2 Present and Expected Future Space Missions 707 18.5.3 Promising Antenna Concepts and Technologies 708 18.6 Enable Sharing the Same Aperture for Multiband and Multipurpose Antennas 709 18.6.1 Problem Area and Challenges 709 18.6.2 Present and Expected Future Space Missions 710 18.6.3 Promising Antenna Concepts and Technologies 710 18.7 Increase the Competitiveness of Well-Established Antenna Products 710 18.7.1 Problem Area and Challenges 710 18.7.2 Present and Expected Future Space Missions 711 18.7.3 Promising Antenna Concepts and Technologies 712 18.8 Enable Single-Beam In-Flight Coverage/Polarization Reconfiguration 713 18.8.1 Problem Area and Challenges 713 18.8.2 Present and Expected Future Space Missions 714 18.8.3 Promising Antenna Concepts and Technologies 714 18.9 Enable Active Antennas at Affordable Cost 715 18.9.1 Problem Area and Challenges 715 18.9.2 Present and Expected Future Space Missions 717 18.9.3 Promising Antenna Concepts and Technologies 718 18.10 Develop Innovative Antennas for Future Earth Observation and Science Instruments 724 18.10.1 Problem Area and Challenges 724 18.10.2 Present and Expected Future Space Missions 725 18.10.3 Promising Antenna Concepts and Technologies 729 18.11 Evolve Towards Mass Production of Satellite and User Terminal Antennas 732 18.11.1 Problem Area and Challenges 732 18.11.2 Present and Expected Future Space Missions 732 18.11.3 Promising Antenna Concepts and Technologies 732 18.12 Technology Push for Enabling New Missions 734 18.12.1 Problem Area and Challenges 734 18.12.2 Promising Antenna Concepts and Technologies 734 18.13 Develop New Approaches for Satellite/Antenna Modelling and Testing 735 18.13.1 Problem Area and Challenges 735 18.13.2 Promising Antenna Concepts and Technologies 736 18.14 Conclusions 737 Acronyms 738 Acknowledgements 740 References 740 Index 741

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Book SynopsisThis unique treatment systematically interprets a spectrum of importance measures to provide a comprehensive overview of their applications in the areas of reliability, network, risk, mathematical programming, and optimization. Investigating the precise relationships among various importance measures, it describes how they are modelled and combined with other design tools to allow users to solve readily many real-world, large-scale decision-making problems. Presenting the state-of-the-art in network analysis, multistate systems, and application in modern systems, this book offers a clear and complete introduction to the topic. Through describing the reliability importance and the fundamentals, it covers advanced topics such as signature of coherent systems, multi-linear functions, and new interpretation of the mathematical programming problems. Key highlights: Generalizes the concepts behind importance measures (such as sensitivity and perturbation analysiTrade Review“It will definitely be very useful for those interested in studying various structures.” (Computing Reviews, 5 November 2012) Table of ContentsPreface xv References xvii Acknowledgements xix Part One INTRODUCTION and BACKGROUND 1 Introduction 2 1 Introduction to Importance Measures 5 References 11 2 Fundamentals of Systems Reliability 13 2.1 Block Diagrams 13 2.2 Structure Functions 14 2.3 Coherent Systems 17 2.4 Modules within a Coherent System 18 2.5 Cuts and Paths of a Coherent System 19 2.6 Critical Cuts and Critical Paths of a Coherent System 21 2.7 Measures of Performance 23 2.7.1 Reliability for a mission time 24 2.7.2 Reliability function (of time t) 25 2.7.3 Availability function 27 2.8 Stochastic Orderings 28 2.9 Signature of Coherent Systems 28 2.10 Multilinear Functions and Taylor (Maclaurin) Expansion 31 2.11 Redundancy 32 2.12 Reliability Optimization and Complexity 33 2.13 Consecutive-k-out-of-n Systems 34 2.14 Assumptions 35 References 36 Part Two PRINCIPLES of IMPORTANCE MEASURES 39 Introduction 40 3 The Essence of Importance Measures 43 3.1 ImportanceMeasures in Reliability 43 3.2 Classifications 44 3.3 c-type and p-type ImportanceMeasures 45 3.4 ImportanceMeasures of a Minimal Cut and a Minimal Path 45 3.5 Terminology 45 References 46 4 Reliability Importance Measures 47 4.1 The B-reliability Importance 47 4.1.1 The B-reliability importance for system functioning and for system failure 52 4.1.2 The criticality reliability importance 52 4.1.3 The Bayesian reliability importance 53 4.2 The FV Reliability Importance 53 4.2.1 The c-type FV (c-FV) reliability importance 54 4.2.2 The p-type FV (p-FV) reliability importance 54 4.2.3 Decomposition of state vectors 54 4.2.4 Properties 56 References 57 5 Lifetime Importance Measures 59 5.1 The B-time-dependent-lifetime Importance 59 5.1.1 The criticality time-dependent lifetime importance 61 5.2 The FV Time-dependent Lifetime Importance 61 5.2.1 The c-FV time-dependent lifetime importance 61 5.2.2 The p-FV time-dependent lifetime importance 63 5.2.3 Decomposition of state vectors 64 5.3 The BP Time-independent Lifetime Importance 64 5.4 The BP Time-dependent Lifetime Importance 69 5.5 Numerical Comparisons of Time-dependent Lifetime ImportanceMeasures 69 5.6 Summary 71 References 72 6 Structure Importance Measures 73 6.1 The B-i.i.d. Importance and B-structure Importance 73 6.2 The FV Structure Importance 76 6.3 The BP Structure Importance 76 6.4 Structure ImportanceMeasures Based on the B-i.i.d. importance 79 6.5 The Permutation Importance and Permutation Equivalence 80 6.5.1 Relations to minimal cuts and minimal paths 81 6.5.2 Relations to systems reliability 83 6.6 The Domination Importance 85 6.7 The Cut Importance and Path Importance 86 6.7.1 Relations to the B-i.i.d. importance 87 6.7.2 Computation 89 6.8 The Absoluteness Importance 91 6.9 The Cut-path Importance,Min-cut Importance, and Min-path Importance 92 6.10 The First-term Importance and Rare-event Importance 93 6.11 c-type and p-type of Structure ImportanceMeasures 93 6.12 Structure ImportanceMeasures for Dual Systems 94 6.13 Dominant Relations among ImportanceMeasures 96 6.13.1 The absoluteness importance with the domination importance 96 6.13.2 The domination importance with the permutation importance 96 6.13.3 The domination importance with the min-cut importance and min-path importance 96 6.13.4 The permutation importance with the FV importance 96 6.13.5 The permutation importance with the cut-path importance, min-cut importance, and min-path importance 100 6.13.6 The cut-path importance with the cut importance and path importance 101 6.13.7 The cut-path importance with the B-i.i.d. importance 101 6.13.8 The B-i.i.d. importance with the BP importance 102 6.14 Summary 102 References 105 7 ImportanceMeasures of Pairs and Groups of Components 107 7.1 The Joint Reliability Importance and Joint Failure Importance 107 7.1.1 The joint reliability importance of dependent components 110 7.1.2 The joint reliability importance of two gate events 110 7.1.3 The joint reliability importance for k-out-of-n systems 111 7.1.4 The joint reliability importance of order k 111 7.2 The Differential ImportanceMeasure 112 7.2.1 The first-order differential importance measure 112 7.2.2 The second-order differential importance measure 113 7.2.3 The differential importance measure of order k 114 7.3 The Total Order Importance 114 7.4 The Reliability AchievementWorth and Reliability ReductionWorth 115 References 116 8 ImportanceMeasures for Consecutive-k-out-of-n Systems 119 8.1 Formulas for the B-importance 119 8.1.1 The B-reliability importance and B-i.i.d. importance 119 8.1.2 The B-structure importance 122 8.2 Patterns of the B-importance for Lin/Con/k/n Systems 123 8.2.1 The B-reliability importance 123 8.2.2 The uniform B-i.i.d. importance 124 8.2.3 The half-line B-i.i.d. importance 126 8.2.4 The nature of the B-i.i.d. importance patterns 126 8.2.5 Patterns with respect to p 128 8.2.6 Patterns with respect to n 129 8.2.7 Disproved patterns and conjectures 131 8.3 Structure ImportanceMeasures 135 8.3.1 The permutation importance 135 8.3.2 The cut-path importance 135 8.3.3 The BP structure importance 135 8.3.4 The first-term importance and rare-event importance 136 References 137 Part Three IMPORTANCE MEASURES for RELIABILITY DESIGN 139 Introduction 140 References 141 9 Redundancy Allocation 143 9.1 Redundancy ImportanceMeasures 144 9.2 A Common Spare 145 9.2.1 The redundancy importance measures 145 9.2.2 The permutation importance 147 9.2.3 The cut importance and path importance 147 9.3 Spare Identical to the Respective Component 148 9.3.1 The redundancy importance measures 148 9.3.2 The permutation importance 149 9.4 Several Spares in a k-out-of-n System 150 9.5 Several Spares in an Arbitrary Coherent System 150 9.6 Cold Standby Redundancy 152 References 152 10 Upgrading System Performance 155 10.1 Improving Systems Reliability 156 10.1.1 Same amount of improvement in component reliability 156 10.1.2 A fractional change in component reliability 157 10.1.3 Cold standby redundancy 158 10.1.4 Parallel redundancy 158 10.1.5 Example and discussion 158 10.2 Improving Expected System Lifetime 159 10.2.1 A shift in component lifetime distributions 160 10.2.2 Exactly one minimal repair 160 10.2.3 Reduction in the proportional hazards 167 10.2.4 Cold standby redundancy 168 10.2.5 A perfect component 170 10.2.6 An imperfect repair 170 10.2.7 A scale change in component lifetime distributions 171 10.2.8 Parallel redundancy 171 10.2.9 Comparisons and numerical evaluation 172 10.3 Improving Expected System Yield 174 10.3.1 A shift in component lifetime distributions 175 10.3.2 Exactly one minimal repair / cold standby redundancy / a perfect component / parallel redundancy 180 10.4 Discussion 182 References 182 11 Component Assignment in Coherent Systems 185 11.1 Description of Component Assignment Problems 186 11.2 Enumeration and Randomization Methods 187 11.3 Optimal Design based on the Permutation Importance and Pairwise Exchange 188 11.4 Invariant Optimal and InvariantWorst Arrangements 189 11.5 Invariant Arrangements for Parallel-series and Series-parallel Systems 191 11.6 Consistent B-i.i.d. Importance Ordering and Invariant Arrangements 192 11.7 Optimal Design based on the B-reliability Importance 194 11.8 Optimal Assembly Problems 196 References 197 12 Component Assignment in Consecutive-k-out-of-n and Its Variant Systems 199 12.1 Invariant Arrangements for Con/k/n Systems 199 12.1.1 Invariant optimal arrangements for Lin/Con/k/n systems 200 12.1.2 Invariant optimal arrangements for Cir/Con/k/n systems 200 12.1.3 Consistent B-i.i.d. importance ordering and invariant arrangements 202 12.2 Necessary Conditions for Component Assignment in Con/k/n Systems 204 12.3 Sequential Component Assignment Problems in Con/2/n:F Systems 206 12.4 Consecutive-2 Failure Systems on Graphs 207 12.4.1 Consecutive-2 failure systems on trees 208 12.5 Series Con/k/n Systems 208 12.5.1 Series Con/2/n:F systems 209 12.5.2 Series Lin/Con/k/n:G systems 209 12.6 Consecutive-k-out-of-r-from-n Systems 211 12.7 Two-dimensional and Redundant Con/k/n Systems 213 12.7.1 Con/(r, k)/(r, n) systems 214 12.8 Miscellaneous 216 References 217 13 B-importance based Heuristics for Component Assignment 219 13.1 The Kontoleon Heuristic 219 13.2 The LK Type Heuristics 221 13.2.1 The LKA heuristic 221 13.2.2 Another three LK type heuristics 221 13.2.3 Relation to invariant optimal arrangements 221 13.2.4 Numerical comparisons of the LK type heuristics 224 13.3 The ZK Type Heuristics 225 13.3.1 Four ZK type heuristics 225 13.3.2 Relation to invariant optimal arrangements 227 13.3.3 Comparisons of initial arrangements 227 13.3.4 Numerical comparisons of the ZK type heuristics 229 13.4 The B-importance based Two-stage Approach 229 13.4.1 Numerical comparisons with the GAMS/CoinBomin solver and enumeration method 230 13.4.2 Numerical comparisons with the randomization method 230 13.5 The B-importance based Genetic Local Search 231 13.5.1 The description of algorithm 232 13.5.2 Numerical comparisons with the B-importance based two-stage approach and a genetic algorithm 235 13.6 Summary and Discussion 236 References 238 Part Four RELATIONS and GENERALIZATIONS 241 Introduction 242 14 Comparisons of Importance Measures 245 14.1 Relations to the B-importance 245 14.2 Rankings of Reliability ImportanceMeasures 247 14.2.1 Using the permutation importance 247 14.2.2 Using the permutation importance and joint reliability importance 249 14.2.3 Using the domination importance 250 14.2.4 Summary 250 14.3 ImportanceMeasures for Some Special Systems 250 14.4 Computation of ImportanceMeasures 251 References 253 15 Generalizations of Importance Measures 255 15.1 Noncoherent Systems 255 15.1.1 Binary monotone systems 256 15.2 Multistate Coherent Systems 257 15.2.1 The μ, _ B-importance 258 15.2.2 The μ, _ cut importance 259 15.3 Multistate Monotone Systems 261 15.3.1 The permutation importance 261 15.3.2 The utility B-reliability importance 262 15.3.3 The utility-decomposition reliability importance 262 15.3.4 The utility B-structure importance, joint structure importance, and joint reliability importance 263 15.3.5 The B-importance, FV importance, reliability achievement worth, and reliability reduction worth with respect to system mean unavailability and mean performance 265 15.4 Binary Type Multistate Monotone Systems 266 15.4.1 The B-t.d.l. importance, BP t.i.l. importance, and L1 t.i.l. importance 267 15.5 Summary of ImportanceMeasures for Multistate Systems 268 15.6 Continuum Systems 270 15.7 Repairable Systems 272 15.7.1 The B-availability importance 272 15.7.2 The c-FV unavailability importance 273 15.7.3 The BP availability importance 273 15.7.4 The L1 t.i.l. importance 274 15.7.5 Simulation-based importance measures 275 15.8 Applications in the Power Industry 276 References 277 Part Five BROAD IMPLICATIONS to RISK and MATHEMATICAL PROGRAMMING 281 Introduction 282 References 283 16 Networks 285 16.1 Network Flow Systems 285 16.1.1 The edge importance measures in a network flow system 286 16.1.2 The edge importance measures for a binary monotone system 288 16.1.3 The B-reliability importance, FV reliability importance, reliability reduction worth, and reliability achievement worth 289 16.1.4 The flow-based importance and impact-based importance 290 16.2 K-terminal Networks 291 16.2.1 Importance measures of an edge 293 16.2.2 A K-terminal optimization problem 295 References 295 17 Mathematical Programming 297 17.1 Linear Programming 297 17.1.1 Basic concepts 298 17.1.2 The simplex algorithm 300 17.1.3 Sensitivity analysis 301 17.2 Integer Programming 303 17.2.1 Basic concepts and branch-and-bound algorithm 303 17.2.2 Branch-and-bound using linear programming relaxations 306 17.2.3 Mixed integer nonlinear programming 309 References 309 18 Sensitivity Analysis 311 18.1 Local Sensitivity and Perturbation Analysis 311 18.1.1 The B-reliability importance 311 18.1.2 The multidirectional sensitivity measure 312 18.1.3 The multidirectional differential importance measure and total order importance 317 18.1.4 Perturbation analysis 318 18.2 Global Sensitivity Analysis 319 18.2.1 ANOVA-decomposition based global sensitivity measures 320 18.2.2 Elementary effect methods and derivative-based global sensitivity measures 323 18.2.3 Relationships between the ANOVA-decomposition-based and the derivativebased sensitivity measures 326 18.2.4 The case of random input variables 327 18.2.5 Moment-independent sensitivity measures 328 18.3 Systems reliability subject to uncertain component reliability 330 18.3.1 Software Reliability 332 18.4 Broad applications 335 References 336 19 Risk and Safety in Nuclear Power Plants 339 19.1 Introduction to Probabilistic Risk Analysis and Probabilistic Safety Assessment 339 19.2 Probabilistic (Local) ImportanceMeasures 340 19.3 Uncertainty and Global Sensitivity Measures 342 19.4 A Case Study 343 19.5 Review of Applications 345 19.6 System Fault Diagnosis and Maintenance 347 References 348 Afterword 350 References 354 APPENDIX 355 A Proofs 357 A.1 Proof of Theorem 8.2.7 357 A.2 Proof of Theorem 10.2.10 358 A.3 Proof of Theorem 10.2.17 359

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Book SynopsisA comprehensive introduction to M2M Standards and systems architecture, from concept to implementation Focusing on the latest technological developments, M2M Communications: A Systems Approach is an advanced introduction to this important and rapidly evolving topic. It provides a systems perspective on machine-to-machine services and the major telecommunications relevant technologies. It provides a focus on the latest standards currently in progress by ETSI and 3GPP, the leading standards entities in telecommunication networks and solutions. The structure of the book is inspired by ongoing standards developments and uses a systems-based approach for describing the problems which may be encountered when considering M2M, as well as offering proposed solutions from the latest developments in industry and standardization. The authors provide comprehensive technical information on M2M architecture, protocols and applications, especially examining M2M service aTable of ContentsForeword List of Contributors List of Acronyms 1 Introduction to M2M 1.1 What is M2M? 1.2 The Business of M2M 1.3 Accelerating M2M Maturity 1.3.1 High-Level M2M Frameworks 1.3.2 Policy and Government Incentives 1.4 M2M Standards 1.4.1 Which Standards for M2M? 1.5 Roadmap of the Book References Part I M2M CURRENT LANDSCAPE 2 The Business of M2M 2.1 The M2M Market 2.1.1 Healthcare 2.1.2 Transportation 2.1.3 Energy 2.2 The M2M Market Adoption: Drivers and Barriers 2.3 The M2M Value Chain 2.4 Market Size Projections 2.5 Business Models 2.5.1 Network Operator- or CSP-Led Model 2.5.2 MVNO-Led Model 2.5.3 Corporate Customer-Led Model 2.6 M2M Business Metrics 2.7 Market Evolution Reference 3 Lessons Learned from Early M2M Deployments 3.1 Introduction 3.2 Early M2M Operational Deployments 3.2.1 Introduction 3.2.2 Early M2M Operational Deployment Examples 3.2.3 Common Questions in Early M2M Deployments 3.2.4 Possible Optimization of M2M Deployments 3.3 Chapter Conclusion Reference Part II M2M ARCHITECTURE AND PROTOCOLS 4 M2M Requirements and High-Level Architectural Principles 4.1 Introduction 4.2 Use-Case-Driven Approach to M2M Requirements 4.2.1 What is a Use Case? 4.2.2 ETSI M2M Work on Use Cases 4.2.3 Methodology for Developing Use Cases 4.3 Smart Metering Approach in ETSI M2M 4.3.1 Introduction 4.3.2 Typical Smart Metering Deployment Scenario 4.4 eHealth Approach in ETSI M2M 4.4.1 Introduction 4.5 ETSI M2M Service Requirements: High-Level Summary and Applicability to Different Market Segments 4.6 Traffic Models-/Characteristics-Approach to M2M Requirements and Considerations for Network Architecture Design 4.6.1 Why Focus on Wireless Networks? 4.7 Description of M2M Market Segments/Applications 4.7.1 Automotive 4.7.2 Smart Telemetry 4.7.3 Surveillance and Security 4.7.4 Point of Sale (PoS) 4.7.5 Vending Machines 4.7.6 eHealth 4.7.7 Live Video 4.7.8 Building Automation 4.7.9 M2M Industrial Automation 4.8 M2M Traffic Characterization 4.8.1 Detailed Traffic Characterization for Smart Metering 4.8.2 Global Traffic Characterization 4.9 High-Level Architecture Principles for M2M Communications 4.10 Chapter Conclusions References 5 ETSI M2M Services Architecture 5.1 Introduction 5.2 High-Level System Architecture 5.3 ETSI TC M2M Service Capabilities Framework 5.4 ETSI TC M2M Release 1 Scenarios 5.5 ETSI M2M Service Capabilities 5.5.1 Reachability, Addressing, and Repository Capability (xRAR) 5.5.2 Remote Entity Management Capability (x REM) 5.5.3 Security Capability (xSEC) 5.6 Introducing REST Architectural Style for M2M 5.6.1 Introduction to REST 5.6.2 Why REST for M2M? 5.6.3 REST Basics 5.6.4 Applying REST to M2M 5.6.5 Additional Functionalities 5.7 ETSI TC M2M Resource-Based M2M Communication and Procedures 5.7.1 Introduction 5.7.2 Definitions Used in this Section 5.7.3 Resource Structure 5.7.4 Interface Procedures 5.8 Chapter Conclusion References 6 M2M Optimizations in Public Mobile Networks 6.1 Chapter Overview 6.2 M2M over a Telecommunications Network 6.2.1 Introduction 6.2.2 M2M Communication Scenarios 6.2.3 Mobile or Fixed Networks 6.2.4 Data Connections for M2M Applications 6.3 Network Optimizations for M2M 6.3.1 Introduction 6.3.2 3GPP Standardization of Network Improvements for Machine Type Communications 6.3.3 Cost Reduction 6.3.4 M2M Value-Added Services 6.3.5 Numbering, Identifiers, and Addressing 6.3.6 Triggering Optimizations 6.3.7 Overload and Congestion Control References 7 The Role of IP in M2M 7.1 Introduction 7.1.1 IPv6 in Brief 7.1.2 Neighbor Discovery Protocol 7.2 IPv6 for M2M 7.3 6LoWPAN 7.3.1 Framework 7.3.2 Header Compression 7.3.3 Neighbor Discovery 7.4 Routing Protocol for Low-Power and Lossy Networks (RPL) 7.4.1 RPL Topology 7.5 CoRE 7.5.1 Message Formats 7.5.2 Transport Protocol 7.5.3 REST Architecture References 8 M2M Security 8.1 Introduction 8.1.1 Security Characteristics of Cellular M2M 8.2 Trust Relationships in the M2M Ecosystem 8.3 Security Requirements 8.3.1 Customer/M2M Device User 8.3.2 Access Network Provider 8.3.3 M2M Service Provider 8.3.4 Application Provider 8.3.5 Bootstrapping Requirements 8.4 Which Types of Solutions are Suitable? 8.4.1 Approaches Against Hijacking 8.4.2 Public Key Solutions 8.4.3 Smart Card-Based Solutions 8.4.4 Methods Based on Pre-Provisioned Symmetric Keys 8.4.5 Protocol for Automated Bootstrapping Based on Identity-Based Encryption 8.4.6 Security for Groups of M2M Devices 8.5 Standardization Efforts on Securing M2M and MTC Communications 8.5.1 ETSI M2M Security 8.5.2 3GPP Security Related to Network Improvements for Machine Type Communications References 9 M2M Terminals and Modules 9.1 M2M Module Categorization 9.1.1 Access Technology 9.1.2 Physical Form Factors 9.2 Hardware Interfaces 9.2.1 Power Interface 9.2.2 USB (Universal Serial Bus) Interface 9.2.3 UART (Universal Asynchronous Receiver/ Transmitter) Interface 9.2.4 Antenna Interface 9.2.5 UICC (Universal Integrated Circuit Card) Interface 9.2.6 GPIO (General-Purpose Input/Output Port) Interface 9.2.7 SPI (Serial Peripheral Interface) Interface 9.2.8 I2C (Inter-Integrated Circuit Bus) Interface 9.2.9 ADC (Analog-to-Digital Converter) Interface 9.2.10 PCM (Pulse Code Modulation) Interface 9.2.11 PWM (Pulse Width Modulation) Interface 9.2.12 Analog Audio Interface 9.3 Temperature and Durability 9.4 Services 9.4.1 Application Execution Environment 9.4.2 Connectivity Services 9.4.3 Management Services 9.4.4 Application Services 9.5 Software Interface 9.5.1 AT Commands 9.5.2 SDK Interface 9.6 Cellular Certification 9.6.1 Telecom Industry Certification 9.6.2 MNO Certification 10 Smart Cards in M2M Communication 10.1 Introduction 10.2 Security and Privacy Issues in M2M Communication 10.3 The Grounds for Hardware-Based Security Solutions 10.4 Independent Secure Elements and Trusted Environments 10.4.1 Trusted Environments in M2M Devices 10.4.2 Trusting Unknown Devices: The Need for Security Certification 10.4.3 Advantages of the Smart Card Model 10.5 Specific Smart Card Properties for M2M Environments 10.5.1 Removable Smart Cards versus Embedded Secure Elements 10.5.2 UICC Resistance to Environmental Constraints 10.5.3 Adapting the Card Application Toolkit to Unattended Devices 10.5.4 Reaching UICC Peripheral Devices with Toolkit Commands 10.5.5 Confidential Remote Management of Third-Party Applications 10.6 Smart Card Future Evolutions in M2M Environments 10.6.1 UICC-Based M2M Service Identity Module Application 10.6.2 Internet Protocol Integration of the UICC 10.7 Remote Administration of M2M Secure Elements 10.7.1 Overview 10.7.2 Late Personalization of Subscription 10.7.3 Remote Management of Subscriptions on the Field References Part III BOOK CONCLUSIONS AND FUTURE VISION 11 Conclusions Index

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Book SynopsisLogically ordered to follow the order of the blocks encountered along a receiver or a transmitter path in a communication platform, this book provides an introduction to system performance metrics, followed by topics on RF/Analog modeling, and simulation examples to support the modeling theory.Table of ContentsPreface xi Acknowledgments xiii About the Author xv 1 Introduction to Communication System-on-Chip, RF Analog Front-End, OFDM Modulation, and Performance Metrics 1 1.1 Communication System-on-Chip 1 1.1.1 Introduction 1 1.1.2 CMOS Technology 3 1.1.3 Coexistence Issues 4 1.2 RF AFE Overview 6 1.2.1 Introduction 6 1.2.2 Superheterodyne Transceiver 8 1.2.3 Homodyne Transceiver 10 1.2.4 Low-IF Transceiver 11 1.2.5 Analog Baseband Filter Order versus ADC Dynamic Range 12 1.2.6 Digital Compensation of RF Analog Front-End Imperfections 13 1.3 OFDM Modulation 14 1.3.1 OFDM as a Multicarrier Modulation 14 1.3.2 Fourier Transform and Orthogonal Subcarriers 15 1.3.3 Channel Estimation and Equalization in Frequency Domain 18 1.3.4 Pilot-Tones 20 1.3.5 Guard Interval 21 1.3.6 Windowed OFDM 21 1.3.7 Adaptive Transmission 22 1.3.8 OFDMA for Multiple Access 23 1.3.9 Scalable OFDMA 23 1.3.10 OFDM DBB Architecture 24 1.3.11 OFDM-Based Standards 27 1.4 SNR, EVM, and 1.4.1 Bit Error Rate 27 1.4.2 SNR versus EVM 28 1.4.3 SNR versus E 1.4.4 Complex Baseband Representation 32 References 34 Eb/N0 Definitions and Relationship 27b/N0 31 2 RF Analog Impairments Description and Modeling 37 2.1 Introduction 37 2.2 Thermal Noise 38 2.2.1 Additive White Gaussian Noise 38 2.2.2 Noise Figure and Sensitivity 40 2.2.3 Cascaded Noise Voltage in IC Design 41 2.2.4 AWGN in Simulations 42 2.2.5 Flicker Noise and AWGN Modeling 43 2.3 Oscillator Phase Noise 44 2.3.1 Description and Impact on the System 44 2.3.2 Phase Noise Modeling in the Frequency Domain 45 2.3.3 Simulation in Temporal Domain 49 2.3.4 SNR Limitation due to the Phase Noise 50 2.3.5 Impact of Phase Noise in OFDM 52 2.4 Sampling Jitter 57 2.4.1 Jitter Definitions 57 2.4.2 Sampling Jitter and Phase Noise Relationship 58 2.4.3 SNR Limitation due to Sampling Jitter 61 2.4.4 Impact of Sampling Jitter in OFDM 63 2.4.5 Sampling Jitter Modeling 63 2.5 Carrier Frequency Offset 64 2.5.1 Description 64 2.5.2 Impact of CFO in OFDM 65 2.6 Sampling Frequency Offset 67 2.6.1 Description 67 2.6.2 Impact of SFO in OFDM 68 2.7 I and Q Mismatch 71 2.7.1 Description 71 2.7.2 IQ Mismatch Modeling 76 2.7.3 SNR Limitation due to IQ Mismatch 76 2.7.4 Impact of IQ Mismatch in OFDM 78 2.8 DAC/ADC Quantization Noise and Clipping 79 2.8.1 SNR Limitation due to the Quantization Noise and Clipping Level 79 2.8.2 Impact of Converter Clipping Level in OFDM 82 2.8.3 DAC and ADC Dynamic Range in OFDM 84 2.8.4 DAC and ADC Modeling 86 2.9 IP2 and IP3: Second- and Third-Order Nonlinearities 87 2.9.1 Harmonics (Single-Tone Test) 87 2.9.2 Intermodulation Distortion (Two-Tone Test) 89 2.9.3 Receiver Performance Degradation due to the Non-linearities 92 2.9.4 Impact of Third-Order Nonlinearity in OFDM 95 2.9.5 Simulation in Complex Baseband 98 2.10 Power Amplifier Distortion 99 2.10.1 PA Modeling 99 2.10.2 Impact of PA Distortions in OFDM 102 References 104 3 Simulation of the RF Analog Impairments Impact on Real OFDM-Based Transceiver Performance 107 3.1 Introduction 107 3.2 WLAN and Mobile WiMAX PHY Overview 108 3.2.1 WLAN: Standard IEEE 802.11a/g 108 3.2.2 Mobile WiMAX: Standard IEEE 802.16e 109 3.3 Simulation Bench Overview 110 3.3.1 WiFi and WiMAX OFDM Transceiver Modeling 110 3.3.2 EVM Estimation as Performance Metric 112 3.3.3 EVM versus SNR Simulations in AWGN Channel 113 3.4 WiFi OFDM and Mobile WiMAX Signals PAPR 116 3.5 Transmitter Impairments Simulation 117 3.5.1 Introduction 117 3.5.2 DAC Clipping and Resolution 118 3.5.3 I and Q Mismatch 121 3.5.4 RF Oscillator Phase Noise 125 3.5.5 Power Amplifier Distortion 130 3.5.6 Transmitter Complete Simulation 133 3.6 Receiver Impairments Simulation 134 3.6.1 Introduction 134 3.6.2 Carrier Frequency Offset 135 3.6.3 Sampling Frequency Offset 140 3.6.4 Linearity: IIP2 and IIP3 146 3.6.5 I and Q Mismatch 154 3.6.6 RF Oscillator Phase Noise and Reciprocal Mixing 154 3.6.7 Sampling Jitter 156 3.6.8 ADC Clipping and Resolution 158 3.6.9 Receiver Complete Simulation 160 3.7 Adaptive Modulation Illustration 162 3.8 Summary 164 References 164 4 Digital Compensation of RF Analog Impairments 167 4.1 Introduction 167 4.2 CFO Estimation and Correction 168 4.2.1 CFO Estimation Principle 168 4.2.2 CFO Estimation in the Time Domain 170 4.2.3 CFO Estimation in the Frequency Domain 172 4.2.4 CFO Correction 175 4.3 SFO Estimation and Correction 176 4.3.1 SFO Estimation Principle 176 4.3.2 SFO Estimation 178 4.3.3 SFO Correction 181 4.3.4 Joint SFO and CFO Estimation 181 4.4 IQ Mismatch Estimation and Correction 183 4.4.1 Principle 183 4.4.2 Effect of the Channel 186 4.4.3 Simulation Results 187 4.5 Power Amplifier Linearization 190 4.5.1 Digital Predistortion Principle 190 4.5.2 Memory Polynomial Predistortion 191 4.5.3 Polynomial Coefficients Computation 192 4.5.4 Simulation Results 193 4.6 Summary 196 References 197 Index 199

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Book SynopsisComplete and comprehensive manual for eliciting, defining, and managing needs and requirements, integration, verification, and validation across the lifecycle The INCOSE Needs and Requirements Manual presents product development and systems engineering practices, activities, and artifacts from the perspective of needs, requirements, verification, and validation across the system lifecycle. Composed of 16 chapters, this book provides practical guidance to help organizations understand the importance of lifecycle concepts, needs, requirements, verification, and validation activities, enabling them to successfully and effectively implement these activities during product development, systems engineering, and project management. The parent handbook published by Wiley, INCOSE Systems Engineering Handbook, divides the system lifecycle into a series of processes, with each process described in terms of a series of activities. This Manual provides more detail needed by practitioners to success

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Book SynopsisMODERN FERRITES, Volume 2 A robust exploration of the basic principles of ferrimagnetic and their applications In Modern Ferrites: Volume 2, renowned researcher and educator, Vincent G. Harris delivers a comprehensive overview of ferrimagnetic phenomena and discussions of select applications of modern ferrite materials in emerging technologies and applications. Volume 2 explores fundamental properties of ferrite systems, including their structure, chemistry, and magnetism, as well as practical applications, such as permanent magnets; inductors, inverters, and filters; and their use in emerging applications as metamaterials, multiferroics, and biomedical technologies. In addition to the properties of ferrites, the included resources explore the processing, structure, and property relationships in ferrites as nanoparticles, thin and thick films, compacts, and crystals. The authors discuss how these relationships are key to realizing practical device applicat

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Book SynopsisA fast and easy way for visual learners to get a grip on Photoshop Elements Are you a visual learner? Do you prefer a single, crystal-clear screenshot showing you how to do something to a long-winded explanation telling you how to do it? If so, then this book is for you. Open up Teach Yourself VISUALLY Photoshop Elements and you'll find vibrant, step-by-step screenshots showing you how to master over 100 Photoshop Elements tasks. Each task-based spread covers one technique at a time, ensuring you get up and running fast. You'll learn how to: Organize, import, save, and print your photosEnhance the lighting and color of pictures that need a little sprucing upApply cool effects that make your photos more lively and interestingThe book breaks big topics down into bite-sized modules with succinct explanations, walking you through every step you need to take. The full-color screenshots demonstrate each task, and helpful sidebars offer practical, hands-on tips and tricks you'll use every timTable of ContentsChapter 1 Getting Started Introducing Photoshop Elements 2023 4 Understanding Digital Images 6 Start Photoshop Elements 8 Explore the Editor Workspace 9 Tour the Organizer Workspace 10 Switch Between the Organizer and the Editor 11 Introducing the Photoshop Elements Tools 12 Switch Editing Modes 14 Work with Tools 16 Work with Panels 18 Set Program Preferences 20 View Rulers and Guides 22 Chapter 2 Importing and Opening Digital Images Get Photos for Your Projects 26 Import Photos from a Digital Camera or Card Reader 28 Import Photos from a Scanner 30 Open a Photo 32 Create a Blank Image 34 Save an Image 36 Print Photos 38 Create a Photo Panorama 40 Duplicate a Photo 42 Close a Photo 43 Chapter 3 Applying Basic Image Edits Manage Open Images 46 Using Layouts 48 Using the Zoom Tool 50 Pan the Image 52 Change the Canvas Size 54 Resize an Image by Resampling 56 Crop an Image 58 Straighten an Image 60 Rotate an Image 61 Work in Quick Mode 62 Apply an Effect in Quick Mode 64 Add a Frame in Quick Mode 65 Apply Automatic Enhancements 66 Add a Texture 68 Undo Edits 70 Revert an Image 71 Chapter 4 Using Layers Introducing Layers 74 Create and Add Content to a Layer 76 Hide a Layer 78 Move a Layer 79 Duplicate a Layer 80 Delete a Layer 81 Reorder Layers 82 Change the Opacity of a Layer 84 Link Layers 85 Merge Layers 86 Rename a Layer 87 Create a Fill Layer 88 Blend Layers 90 Chapter 5 Making Selections Select an Area with the Marquee 94 Select an Area with the Lasso 96 Select an Area with the Magic Wand 100 Select an Area with the Quick Selection Tool 102 Select an Area with the Selection Brush 104 Save and Load a Selection 106 Invert a Selection 108 Deselect a Selection 109 Chapter 6 Manipulating Selections Add to or Subtract from a Selection 112 Move a Selection 114 Apply the Content-Aware Move Tool 116 Copy and Paste a Selection 118 Delete a Selection 119 Rotate a Selection 120 Scale a Selection 121 Skew or Distort a Selection 122 Refine the Edge of a Selection 124 Use Feathering to Create a Soft Border 126 Chapter 7 Enhancing Lighting, Color, and Sharpness Adjust Levels 130 Adjust Shadows and Highlights 132 Change Brightness and Contrast 134 Use the Dodge and Burn Tools 136 Sharpen an Image 138 Use the Blur and Sharpen Tools 140 Adjust Skin Color 142 Adjust Color with the Sponge Tool 144 Replace a Color 146 Convert a Color Photo to Black and White 148 Add Color to a Black and White Photo 150 Adjust Colors by Using Color Curves 152 Apply the Auto Smart Tone Tool 154 Chapter 8 Applying Quick and Guided Edits Quickly Fix a Photo 158 Remove Red Eye 160 Remove a Color Cast 162 Restore an Old Photo 164 Improve a Portrait 166 Apply a Lomo Camera Effect 168 Add Motion with Zoom Burst 170 Create a Perfect Pet Pic 172 Create Soft Focus with the Orton Effect 174 Apply a Reflection 176 Make a Meme 178 Create a Vintage Look 180 Chapter 9 Painting and Drawing on Photos Retouch with the Clone Stamp Tool 184 Remove a Spot 186 Set the Foreground and Background Colors 188 Add Color with the Brush Tool 190 Change Brush Styles 192 Use a Brush to Replace a Color 194 Adjust Colors with the Smart Brush 196 Draw a Simple Shape 198 Add an Arrow 200 Apply the Eraser 202 Apply a Gradient 204 Add Content from the Graphics Panel 206 Add Text 208 Modify Text 210 Create Warped Text 212 Draw Text Around a Shape 214 Add a Layer Mask 216 Edit a Layer Mask 218 Chapter 10 Applying Filters and Styles Equalize an Image 222 Create a Negative 223 Blur an Image 224 Distort an Image 226 Turn an Image into Art 228 Turn an Image into a Sketch 230 Create a Print Halftone 232 Add a Drop Shadow to a Layer 234 Apply Other Styles 236 Enhance with an Effect 237 Chapter 11 Organizing Your Photos Introducing the Organizer 240 Open the Organizer 242 Change the View 243 Create a Catalog 244 View Photos in Media View 246 View Photos in Full Screen 248 View File Information 250 Work with Albums 252 Find Photos 254 View Versions of a File 256 Remove a Photo from the Organizer 257 Apply an Instant Fix 258 Perform Other Organization Tasks 260 Index 262

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Book SynopsisTHE ECONOMICS OF MICROGRIDS An incisive and practical exploration of the engineering economics of microgrids In The Economics of Microgrids, a pair of distinguished researchers delivers an expert discussion of the microeconomic perspectives on microgrids in the context of low-carbon, sustainable energy delivery. In the book, readers will explore an engineering economics framework on the investment decisions and capital expenditure analyses required for an assessment of microgrid projects. The authors also examine economic concepts and models for minimizing microgrid operation costs, including the cost of local generation resources and energy purchases from main grids to supply local loads. The book presents economic models for the expansion of microgrids under load and market price uncertainties, as well as discussions of the economics of resilience in microgrids for optimal operation during outages and power disturbances. Readers will also find: A thorough introduction to the engineer

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Book SynopsisMICROGRIDS for COMMERCIAL SYSTEMS This distinct volume provides detailed information on the concepts and applications of the emerging field of microgrids for commercial applications, offering solutions in the design, installation, and operation of this new, cutting-edge technology. The microgrid is defined as Distributed Energy Resources (DER) and interconnected loads with clearly defined electrical boundaries that act as a single controllable entity concerning the grid as per IEEE standard 2030.7-2017. It provides an uninterrupted power supply to end-user loads with high reliability. Commercial systems like IT/ITES, shopping complexes, malls, the banking sector, hospitals, etc., need an uninterrupted input power supply with high reliability. Microgrids are more suitable for commercial systems to service their clients with no service discontinuity. The microgrid enables both connection and disconnection from the grid. That is, the microgrid can operate both in grid-connected and islan

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Book SynopsisADVANCED ULTRA LOW-POWER SEMICONDUCTOR DEVICES Written and edited by a team of experts in the field, this important new volume broadly covers the design and applications of metal oxide semiconductor field effect transistors. This outstanding new volume offers a comprehensive overview of cutting-edge semiconductor components tailored for ultra-low power applications. These components, pivotal to the foundation of electronic devices, play a central role in shaping the landscape of electronics. With a focus on emerging low-power electronic devices and their application across domains like wireless communication, biosensing, and circuits, this book presents an invaluable resource for understanding this dynamic field. Bringing together experts and researchers from various facets of the VLSI domain, the book addresses the challenges posed by advanced low-power devices. This collaborative effort aims to propel engineering innovations and refine the practical implementation ofTable of ContentsPreface xi 1 Subthreshold Transistors: Concept and Technology 1Ball Mukund Mani Tripathi 1.1 Introduction 2 1.2 Major Sources of Leakage and Possible Methods of Prevention 2 1.3 Possibilities and Challenges 12 1.4 Conclusions 21 2 Introduction to Conventional MOSFET and Advanced Transistor TFET 29M. Saravanan, K. Ramkumar, Eswaran Parthasarathy, J. Ajayan and S. Sreejith 2.1 Introduction 30 2.2 Device Structure 30 2.3 TFET Principle of Operation 31 2.4 Material Characterization 33 2.5 Characteristics of TFET 35 2.6 Comparison of OFF-State Characteristics 37 2.7 Phonon Scattering's Impact 39 2.8 ON-State Performance Comparison 40 2.9 Performance Analysis Based on Intrinsic Delay 40 2.10 Bandgap's Effect on Device Performance 41 2.11 MOSFET and TFET Scaling Behaviour 43 2.12 Surface Potential of an N-TFET and N-MOSFET 45 2.13 Professional Advantages of TFET over MOSFET 46 2.14 Conclusion 46 3 Operation Principle and Fabrication of TFET 51Mekonnen Getnet Yirak and Rishu Chaujar 3.1 Introduction 52 3.2 Planar MOSFET's Limitations 54 3.3 Demand for Low Power Operation 55 3.4 TFET: Operation Principle of TFET 56 3.5 TFET: Recent Design Issues in TFET 63 3.6 TFET: Modeling and Application 65 3.7 TFET: Fabrication Perspective 68 3.8 TFET: Applications and Future of Low-Power Electronics 70 3.9 Expected Challenges in Replacing MOSFET with TFET 70 3.10 Conclusion 71 4 Mathematical Modeling of TFET and Its Future Applications: Ultra Low-Power SRAM Circuit and III-IV TFET 77Nayana G H and P. Vimala 4.1 Introduction 78 4.2 Modeling Approaches 78 4.3 Structure 81 4.4 Applications of Tunnel Field-Effect Transistor 83 4.5 Road Ahead for Tunnel Field Effect Transistors 87 5 Analysis of Channel Doping Variation on Transfer Characteristics to High Frequency Performance of F-TFET 91Prabhat Singh and Dharmendra Singh Yadav 5.1 Introduction 92 5.2 Simulated Device Structure and Parameters 93 5.3 DC Characteristics 93 5.4 Analysis of Analog/RF FOMs 98 5.5 Conclusion 101 6 Comparative Study of Gate Engineered TFETs and Optimization of Ferroelectric Heterogate TFET Structure 105Susmitha Kothapalli, Zohmingliana and Brinda Bhowmick 6.1 Introduction 106 6.2 Study of Different TFET Structures 106 6.3 Proposed Structure 109 6.4 Results and Discussion 110 6.5 Conclusion 127 6.6 Future Scope 128 7 State of the Art Tunnel FETs for Low Power Memory Applications 131Arun A. V., Sreelekshmi P. S. and Jobymol Jacob 7.1 Static Random Access Memory 131 7.2 Performance Parameters of SRAM Cell 134 7.3 TFET-Based SRAM Cell Design 135 7.4 Conclusion 159 8 Epitaxial Layer-Based Si/SiGe Hetero-Junction Line Tunnel FETs: A Physical Insight 165Abhishek Acharya, Sourabh Panwar, Shobhit Srivastava and Shashidhara M. 8.1 Fundamental Limitation of CMOS: Tunnel FETs 165 8.2 Working Principle of Tunnel FET 168 8.3 Point and Line TFETs: Tunneling Direction 169 8.4 Perspective of Line TFETs 170 8.5 Analytical Models of Line TFETs 176 8.6 Line TFETs for Analog & Digital Circuits Design 178 8.7 Other Steep Slope Devices 179 8.8 Conclusion 181 9 Investigation of Thermal Performance on Conventional and Junctionless Nanosheet Field Effect Transistors 187Sresta Valasa, Shubham Tayal and Laxman Raju Thoutam 9.1 Introduction 188 9.2 Device Simulation Details 190 9.3 Results and Discussion 192 9.4 Conclusion 201 10 Introduction to Newly Adopted NCFET and Ferroelectrics for Low-Power Application 207Shelja Kaushal 10.1 Introduction 208 10.2 NCFET and Its Design Constraints 209 10.3 NCFET for Low-Power Applications 216 10.4 Summary 226 11 Application of Ferroelectrics: Monolithic-3D Inference Engine with IGZO Based Ferroelectric Thin Film Transistor Synapses 235Sourav De, Maximilian Lederer, Yannick Raffel, David Lehninger, Sunanda Thunder, Michael P.M. Jank, Tarek Ali and Thomas Kämpfe 11.1 Introduction 236 11.2 Ferroelectricity in Hafnium Oxide 241x Contents 11.3 IGZO Based Ferroelectric Thin Film Transistor 245 11.4 Applications in Neural Networks 249 11.5 Conclusion 250 12 Radiation Effects and Their Impact on SRAM Design: A Comprehensive Survey with Contemporary Challenges 261Y. Alekhya, Umakanta Nanda and Chandan Kumar Pandey 12.1 Introduction 261 12.2 Literature Survey 263 12.3 Impact of Radiation Effects on Sram Cells 266 12.4 Results and Discussion 267 12.5 Conclusion 274 13 Final Summary and Future of Advanced Ultra Low Power Metal Oxide Semiconductor Field Effect Transistors 279Young Suh Song, Shiromani Balmukund Rahi, Shahnaz Kossar, Abhishek Kumar Upadhyay, Shubham Tayal, Chandan Kumar Pandey and Biswajit Jena 13.1 Introduction 280 13.2 Challenges in Future Ultra-Low Power Semiconductors 282 13.3 Conclusion 286 References 288 Index 293

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Book SynopsisDRONE TECHNOLOGY This book provides a holistic and valuable insight into the revolutionary world of unmanned aerial vehicles (UAV). The book elucidates the revolutionary and riveting research in the ultramodern domain of drone technologies, drone-enabled IoT applications, and artificial intelligence-based smart surveillance. The book explains the most recent developments in the field, challenges, and future scope of drone technologies. Beyond that, it discusses the importance of a wide range of design applications, drone/UAV development, and drone-enabled smart healthcare systems for smart cities. It describes pioneering work on mitigating cyber security threats by employing intelligent machine learning models in the designing of IoT-aided drones. The book also has a fascinating chapter on application intrusion detection by drones using recurrent neural networks. Other chapters address interdisciplinary fields like artificial intelligence, deep learning, the role of drones in healthTable of ContentsPreface xvii 1 Drone Technologies: State-of-the-Art, Challenges, and Future Scope 1 Arun Agarwal, Chandan Mohanta and Saurabh Narendra Mehta 1.1 Introduction 2 1.2 Forces Acting on a Drone 3 1.3 Principal Axes 3 1.4 Broad Classification of Drones 3 1.4.1 Fixed-Wing Drones 3 1.4.1.1 Advantages 4 1.4.1.2 Disadvantages 5 1.4.2 Lighter-Than-Air Systems 5 1.4.2.1 Advantages 5 1.4.2.2 Disadvantages 6 1.4.3 Multi-Rotor Configuration 6 1.4.3.1 Advantages 6 1.4.3.2 Disadvantages 7 1.5 Military Necessity of Drones 7 1.5.1 Features of Sixth-Generation Fighter Planes 7 1.5.1.1 Introduction 7 1.5.1.2 Cyber Warfare and Cyber Security 9 1.5.1.3 Artificial Intelligence 9 1.5.1.4 Drones and Drone Swarms 10 1.5.1.5 Directed Energy Weapons 10 1.5.2 Pseudo Satellite of HAL 11 1.5.3 Surface to Air Missile vs. Modern Fighter Aircraft 13 1.5.4 Drones as Weapons of Mass Destruction 14 1.6 Conclusion and Future Scope 16 References 17 2 Introduction to Drone Flights—An Eye Witness for Flying Devices to the New Destinations 21 S. Venkata Achuta Rao, P. Srilatha, G.V.R.K. Acharyulu and G. Suryanarayana 2.1 Introduction 22 2.1.1 Brief History 23 2.1.2 The Indomitable Significance of Drone Technology 23 2.1.3 Trends 24 2.2 How Drones Work and Their Anatomy 25 2.2.1 Anatomy of a Drone 25 2.2.1.1 Propellers 25 2.2.1.2 Brushless Motors 26 2.2.1.3 Landing Gear 26 2.2.1.4 Electronic Speed Controllers [ESC] 26 2.2.1.5 Flight Controller 26 2.2.1.6 Receiver 27 2.2.1.7 Transmitter 27 2.2.1.8 GPS Module 27 2.2.1.9 Battery 27 2.2.1.10 Camera 28 2.2.2 Types of Drones 28 2.2.2.1 Sub-System of UAVs 29 2.2.2.2 Other Specific Types of Drones 29 2.2.3 Components of Drones 32 2.2.3.1 Hardware 32 2.2.3.2 Software 33 2.2.3.3 Other Specific Components 33 2.3 Salient Features and Important Codes with Public Awareness with Respect to Safety and Necessary Precautionary Points 36 2.3.1 Safety and Legal Note 36 2.3.2 Public Perception 36 2.3.3 Crew 36 2.3.4 Know Before You Fly 36 2.3.5 Simulation Training 37 2.3.6 Mapping Configuration 37 2.3.7 Mapping BFS Camera and Mapping Camera Mount 37 2.3.8 Equipment to Remove 38 2.3.9 Flight Planning 38 2.3.10 Post Processing Data 39 2.4 Top 10 Stunning Applications of Drone Technology 39 2.4.1 Aerial Photography 40 2.4.2 Shipping and Delivery 40 2.4.3 Geographic Mapping 40 2.4.4 Disaster Management 40 2.4.5 Precision Agriculture 40 2.4.6 Search and Rescue 41 2.4.7 Weather Forecast 41 2.4.8 Wildlife Monitoring 41 2.4.9 Law Enforcement 41 2.4.10 Entertainment 42 2.5 Drones in Enterprises: What Value Do They Add? Work Place Safety and Industry Benchmarks 42 2.5.1 Total Workplace Safety with Drones 43 2.5.2 Future of Drones with Idea Forge’s Industry Benchmarks 43 2.6 Advantages and Disadvantages of Drones 44 2.6.1 Significant Advantages 45 2.6.2 Disadvantages of Drones 45 2.6.3 Significant Disadvantages 46 2.6.4 Best Uses for Drones and Its Applications 46 2.7 Drone Technology as Career and Offered Jobs in the Current Industry 47 2.8 Societal Impact—Commercial Drones 47 2.9 Drones Research Challenges and Solutions 48 2.10 Conclusion 49 References 50 3 Drone/UAV Design Development is Important in a Wide Range of Applications: A Critical Review 53 M. V. Kamal, P. Dileep, G. Sharada, V. Suneetha and M. Gayatri 3.1 Introduction 54 3.2 Classification of Various Categories of Air Drones 55 3.2.1 VTOL and HTOL UAVs 57 3.2.2 Tilt-Body, Tilt-Rotor, and Tilt-Wingducted Fan UAVs 57 3.2.3 Heli-Wing and Helicopter UAVs 58 3.3 Drones Acting on Various Industries 58 3.3.1 Military Drones 58 3.3.2 Medical Drones 58 3.3.3 Agricultural Drones 62 3.4 Conclusions and Future Scope 62 References 63 4 A Comprehensive Study on Design and Control of Unmanned Aerial Vehicles 69 P. Venkateshwar Reddy, P. Srinivasa Rao, M. Hrishikesh and C. Satya Kumar 4.1 Introduction 70 4.2 Classification of Drones 72 4.3 Flight Performance Analysis 75 4.4 Dynamics and Design Objectives of Drones 79 4.4.1 Drone Dynamics 79 4.4.2 Design Objectives and Scaling Laws 80 4.4.3 Energy Utilization 81 4.4.4 Agility and Speed 81 4.4.5 Survivability and Robustness 83 4.4.6 Low-Level Control and Stabilization 83 4.5 Design Methods and Challenges 86 4.5.1 Proposed Solutions for Design Challenges 87 4.6 Guidance, Navigation, and Control of Drones 88 4.7 Conclusion 92 References 93 5 Some Studies of the Latest Artificial Intelligence Applications of Drones are Explored in Detail with Application Phenomena 99 G. Vaitheeswaran, B. Sundaravadivazhagan and Karthikeyan 5.1 Introduction 100 5.2 Evolution of the Drone 101 5.2.1 Military Drones 102 5.2.2 Commercial Drones 103 5.3 Drone Features 104 5.4 AI Meets Drones 105 5.5 Use Cases 109 5.5.1 Army 109 5.5.2 Weather Forecast 111 5.5.3 Industry 112 5.5.4 Agriculture 113 5.5.5 Logistics 113 5.6 Conclusion 115 References 115 6 Drone Technologies: Aviation Strategies, Challenges, and Applications 117 Devshri Satyarthi, K.V. Arya and Manish Dixit 6.1 Introduction 118 6.1.1 Categorization of Unmanned Aerial Vehicle (UAV) 119 6.1.1.1 Classification Based on Size 119 6.1.1.2 Classification Based on Range, Endurance, and Altitude 121 6.1.1.3 Classification Based on Weight 121 6.1.1.4 Classification Based on Engine Type 122 6.1.1.5 Classification Based on Configuration 122 6.1.1.6 Classification Based on Mechanical Design and Analysis 123 6.1.2 Specification of Drones 123 6.2 Drone Technology 124 6.2.1 Drone Monitoring Equipment 125 6.2.2 Drone Countermeasure Equipment 127 6.2.3 Collision Avoidance and Obstacle Detection Technology 129 6.2.4 Flight Controllers, Gyroscope Stabilization, and IMU 129 6.2.5 Drone Propulsion Technology 130 6.2.6 Real-Time Telemetry Flight Parameters 130 6.2.7 No Fly Zone Drone Technology 130 6.2.8 LED Flight Indicators 130 6.2.9 Drones with High Performance Camera 131 6.2.10 Remote Control System and Receiver of UAV 131 6.2.11 Range Extender UAV Technology 131 6.2.12 Video Editing Software 131 6.2.13 Operating Systems in Drone 131 6.2.14 Drone Security and Hacking 131 6.2.15 Modern Top Technology (Drones with Camera) 132 6.2.16 Intelligent Flight Systems 133 6.2.17 Drones For Tracking 133 6.3 India 2021: The Drone Policy and Rules 133 6.3.1 India Policy Guideline for Drones 133 6.3.2 Drone Rules 2021 136 6.4 Unmanned Aerial Vehicle (UAV) or Drone Application 137 6.4.1 Precision Agriculture 137 6.4.1.1 Related Work 138 6.4.1.2 Uses of UAV in Precision Agriculture 139 6.4.1.3 Challenges 140 6.4.1.4 Research Trends 140 6.4.1.5 Future Insights 141 6.4.2 Surveillance Applications of UAVs 141 6.4.2.1 Literature Review 141 6.4.2.2 State-of-the-Art Research 142 6.4.2.3 Product Introduction 142 6.4.2.4 Research Trends and Future Insights 142 6.4.3 Search and Rescue (SAR) 142 6.4.3.1 How SAR Operations Utilize UAVs 143 6.4.3.2 Challenges 143 6.4.3.3 Research Trends 143 6.4.3.4 Future Insights 143 6.4.4 Construction and Infrastructure Inspection 144 6.4.4.1 Literature Review 144 6.4.4.2 Deployment of Drone for Construction and Infrastructure Inspection Applications 144 6.4.4.3 Challenges 144 6.4.4.4 Research Trends 144 6.4.4.5 Future Insights 145 6.4.5 Delivery of Goods 145 6.4.5.1 UAVs-Based Goods Delivery System 145 6.4.5.2 Challenges 145 6.4.5.3 Research Trends 146 6.4.5.4 Future Insights 146 6.5 Conclusion 147 References 147 7 AI Applications of Drones 153 LNC Prakash K., Santosh Kumar Ravva, M.V. Rathnamma and G. Suryanarayana 7.1 Introduction 154 7.2 Review of Literature 159 7.3 AI in Drone Navigation 165 7.4 Companies that Use the AI Drone to Solve Big Problems 166 7.5 Drone Applications Using AI 169 7.6 Issues in the Integration of AI with Drones 176 7.7 Conclusion 177 References 179 8 Applications of Drones—A Review 183 Swathi Gowroju and Santhosh Ramchander N. 8.1 Introduction 184 8.2 Drone Hardware 188 8.3 Components of UAV 189 8.4 Literature Survey 190 8.4.1 Applications of Drones in Aerial Systems 190 8.4.2 Applications of Drones in Oil and Gas Industries 194 8.4.3 Applications of Drones in Military 195 8.4.4 Applications of Drones in Mines 195 8.4.4.1 Underground Mine Geotechnical Characterization 196 8.4.4.2 Underground Mine Rock Size Distribution Analysis 196 8.4.4.3 Underground Coal Mine Gas Detection 196 8.5 Analysis and Discussion 196 Conclusion 203 References 204 9 Drone Enables IoT Applications for Smart Cities 207 R. Santosh Kumar, LNC Prakash K. and G. Suryanarayana 9.1 Introduction to Smart Cities 208 9.2 Components and Characteristics of Smart Cities 209 9.2.1 Smart Healthcare 210 9.2.2 Smart Transportation 210 9.2.3 Smart Pollution Monitoring System 211 9.2.4 Smart Infrastructure and Building 212 9.2.5 Smart Building 212 9.3 The Role of IoT in Smart Cities 213 9.3.1 Road Traffic 213 9.3.2 Smart Parking 214 9.3.3 Public Transport 214 9.3.4 Utilities 215 9.3.4.1 Billing and Smart Meters 215 9.3.4.2 Disclosing Consumption Habits 215 9.3.4.3 Remote Surveillance 215 9.3.5 Waste Management 215 9.3.6 Environment 216 9.3.7 Public Safety 216 9.3.8 Security and Privacy for Smart Cities 216 9.4 General Approach to Implement IoT Solutions in Smart City Design 217 9.5 Challenges in IoT Solutions to Use in Smart City Design 219 9.6 Introduction to Unmanned Aerial Vehicles 221 9.7 Opportunities and Challenges of UAV’s in Smart Cities 222 9.8 Drone-Enabled IoT 224 9.8.1 Drone-Enabled IoT for Disaster Management 224 9.8.2 Drone-Enabled IoT for Public Safety 225 9.8.3 Drone-Enabled IoT for Data Collection 226 9.8.4 Drones and IoT for Improving Life Quality 227 9.8.5 Drone-Enabled IoT for Energy Efficiency 227 9.8.6 Privacy and Security Issues in Drone-Enabled IoT 228 9.9 Conclusion and Future Scope 229 References 229 10 AI-Based Smart Surveillance for Drowning and Theft Detection in Beaches Using Drones 243 V. Sakthivel, Suriya E., Jae Woo Lee and P. Prakash 10.1 Introduction 244 10.2 Literature Survey 244 10.3 Proposed Model 245 10.3.1 Drown Detection by Deep Learning Methods 245 10.3.2 People Alert System Using BLE Beacons 250 10.3.3 Abnormal Event Monitoring for Theft Detection 251 10.4 Deep Learning Model Safeties 252 10.5 Performance Evaluation 254 10.6 Conclusion 254 10.7 Conclusion and Future Work 255 Acknowledgements 256 References 256 11 Algorithms to Mitigate Cyber Security Threats by Employing Intelligent Machine Learning Models in the Design of IoT-Aided Drones 257 Devee Siva Prasad, Pyla Jyothi, G. Suryanarayana and Sachi Nandan Mohanty 11.1 Introduction 258 11.2 Research Methodology 260 11.3 Motivation 260 11.4 Machine Learning for Drone Security 262 11.5 Use of AI in Cyber Security 266 11.6 Use of AI in System to Achieve Robustness, Resilience and Response 267 11.7 NIC Algorithms in Cyber Security 271 11.8 Example Systems for AI and ML Applications for Cyber Security Diagnose 272 11.9 Introduction of New Threats 274 11.10 Areas were Malicious Use of Deepfakes is Trending 276 11.11 Model-Aided Deep Reinforcement Learning for Sample- Efficient UAV Trajectory Design in IoT Networks 276 11.12 Model-Aided Deep Q-Learning 278 11.13 Algorithm Model-Aided Deep Q-Learning Trajectory Design 280 11.13.1 Numerical Results 281 11.14 Machine Learning for Drone Security 282 11.15 Surveillance 283 11.16 Technologies Driving Drones’ Success 284 11.17 Related Work 286 11.18 Drones for Public Safety 289 11.19 Securing Drones 292 11.19.1 Machine and Deep Learning Models 293 11.20 Future Work 294 11.21 Contributions 295 Conclusion 295 References 296 12 IoT-Enabled Unmanned Aerial Vehicle: An Emerging Trend in Precision Farming 301 Gayatri Phade, A. T. Kishore, S. Omkar and M. Suresh Kumar 12.1 Introduction to IoT Enabled UAV 302 12.2 Drones in Precision Farming 306 12.2.1 Types of Agriculture Drones for Precision Agriculture 308 12.2.2 Drone Architecture for Precision Farming 310 12.2.3 IoT-Enabled Drone in Precision Farming 311 12.2.4 Safety and Security in IoT-Enabled Drones in Precision Farming 316 12.2.5 IoT Architecture in Drone 316 12.3 Challenges and Future Scope in IoT-Enabled Drone 319 12.4 Results and Discussion 320 Acknowledgement 322 References 322 13 Unmanned Aerial Vehicle for Land Mine Detection and Illegal Migration Surveillance Support in Military Applications 325 C. Anil Kumar Reddy and B.Venkatesh 13.1 Introduction to Military Drones 326 13.1.1 Unmanned Aerial Vehicle (UAV) 326 13.1.2 UAV Types 329 13.1.2.1 Multi-Rotor Drones 330 13.1.3 Problem Statement 330 13.1.4 Objective 330 13.1.5 Previous Work 331 13.2 Literature Review 331 13.2.1 Need of Drones for Indian Borders 334 13.2.2 UAV Technical Specifications 336 13.3 Methodology of UAV’s in Military Applications 336 13.3.1 Proposed System 336 13.3.2 Methodology 337 13.3.2.1 UAV Work Principle 337 13.3.2.2 UAV Controls and Installation 338 13.3.2.3 Drone Material and Frame 342 13.3.2.4 Program Used/Software Used (e.g., Aurdino) and Data Collection 342 13.3.2.5 Illegal Migration Surveillance with Camera 343 13.3.2.6 Data Collection from Mine Detector and Camera 344 13.3.2.7 Testing Conditions Applied for this Drone 344 13.4 Software Implementation 344 13.4.1 Arduino IDE 345 13.4.2 UAV Program/Coding 345 Appendix A 345 13.5 Conclusion 348 References 348 14 Importance of Drone Technology in Agriculture 351 Karuppiah Natarajan, Karthikeyan R. and Rajalingam S. 14.1 Introduction 352 14.2 Components of a Drone 352 14.3 Study of Natural Resources 355 14.3.1 Study of Natural and Manmade Pastures 357 14.3.2 Monitor Water Resources, Floods, and Droughts 357 14.3.3 Study of Weather Patterns 357 14.3.4 Monitoring of Soil Erosion 358 14.3.5 Cloud Seeding 359 14.4 Soil Fertility Management 359 14.4.1 Management of Soils and Their Fertility 360 14.4.2 Variable-Rate Technology for Soil Fertility Management 361 14.5 Irrigation and Water Management 362 14.5.1 Crop Water Stress Index 363 14.5.2 Drones to Monitor Water Resources 363 14.5.3 Drones to Design an Irrigation System 364 14.6 Crop Disease Identification 365 14.6.1 Monitoring and Identification Using Different Drone Platforms and Peripherals 365 14.6.2 Disease Symptoms 366 14.6.2.1 Sheath Blight 366 14.6.2.2 Narrow Brown Leaf Spot 367 14.7 Pest Control Management 368 14.7.1 Drones Offer a Sustainable Pest Control Solution 368 14.8 Agricultural Drones to Improve Crop Yield Management Efficiency 369 14.9 Issues and Challenges 370 14.9.1 Power Source and Flight Time 370 14.9.2 High Capital Cost 371 14.9.3 The Capacity of the Tank to Carry Fertilizer and Water for Spraying 372 14.9.4 Lack of Technical Skills to Operate, Repair, and Service 372 14.9.5 Job Loss of Existing Farm Workers 372 14.10 Conclusion 372 References 373 15 Network Intrusion Detection of Drones Using Recurrent Neural Networks 375 Yadala Sucharitha, Pundru Chandra Shaker Reddy and G. Suryanarayana 15.1 Introduction 376 15.2 Related Works 378 15.3 Drone Intrusion Detection Methodology 380 15.3.1 Drone RNN 381 15.3.2 Data Collector 382 15.3.3 Centralized-RNN 383 15.3.4 Decision-Maker 383 15.4 Results and Discussion 384 15.4.1 Model Assessment 384 15.4.2 Performance Analysis 384 15.4.3 LSTM_RNN Performance over UNSW-NB 15 Dataset 385 15.5 Conclusion 388 References 388 16 Drone-Enabled Smart Healthcare System for Smart Cities 393 Subasish Mohapatra, Amlan Sahoo, Subhadarshini Mohanty and Sachi Nandan Mohanty 16.1 Introduction 394 16.2 Related Works 397 16.3 Applications of Drones 399 16.4 Suggested Framework 411 16.5 Challenges 415 16.6 Conclusion 418 Future Scopes 419 References 420 17 Drone Delivery 425 V. Sakthivel, Sourav Patel, Jae Woo Lee and P. Prakash 17.1 Introduction 426 17.2 History of Drones 427 17.3 Drone Delivery in Healthcare 432 17.4 Drone Delivery of Food 432 17.5 Drone Delivery in Postal Service 433 17.6 Delivery of Goods 433 Acknowledgements 439 References 439 Index 441

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Book SynopsisPractical Control System Design This book delivers real world experience covering full-scale industrial control design, for students and professional control engineers Inspired by the authors' industrial experience in control, Practical Control System Design: Real World Designs Implemented on Emulated Industrial Systems captures that experience, along with the necessary background theory, to enable readers to acquire the tools and skills necessary to tackle real world control engineering design problems. The book draws upon many industrial projects conducted by the authors and associates; these projects are used as case studies throughout the book, organized in the form of Virtual Laboratories so that readers can explore the studies at their own pace and to their own level of interest. The real-world designs include electromechanical servo systems, fluid storage, continuous steel casting, rolling mill center line gauge control, rocket dynamics and control, crTable of ContentsPreface xix About the Authors xxi Acknowledgements xxiii About the Companion Website xxiv Part I Modelling and Analysis of Linear Systems 1 1 Introduction to Control System Design 3 1.1 Introduction 3 1.2 A Brief History of Control 4 1.3 Digital Control 5 1.4 Our Selection 5 1.5 Thinking Outside the Box 6 1.6 How the Book Is Organised 6 1.7 Testing the Reader’s Understanding 6 1.8 Revision Questions 7 Further Reading 7 2 Control as an Inverse Problem 9 2.1 Introduction 9 2.2 The Elements 9 2.3 Using Eigenvalue Analysis 10 2.4 The Effect of Process and Disturbance Errors 11 2.5 Feedback Control 11 2.6 The Effect of Measurement Noise 12 2.7 Sensitivity Functions 14 2.8 Reducing the Impact of Disturbances and Model Error 14 2.9 Impact of Measurement Noise 14 2.10 Other Useful Sensitivity Functions 14 2.11 Stability (A First Look) 15 2.12 Sum of Sensitivity and Complementary Sensitivity 15 2.13 Revision Questions 16 Further Reading 16 3 Introduction to Modelling 17 3.1 Introduction 17 3.2 Physical Modelling 17 3.2.1 Radio Telescope Positioning 17 3.2.2 Band-Pass Filter 19 3.2.3 Inverted Pendulum 19 3.2.4 Flow of Liquid out of a Tank 20 3.3 State-Space Model Representation 21 3.3.1 Systems Without Zeros 22 3.3.2 Systems Which Depend on Derivatives of the Input 23 3.3.3 Example: State-Space Representation 24 3.4 Linearisation and Approximation 25 3.4.1 Linearisation of Inverted Pendulum Model 26 3.5 Revision Questions 27 Further Reading 28 4 Continuous-Time Signals and Systems 29 4.1 Introduction 29 4.2 Linear Continuous-Time Models 29 4.3 Laplace Transforms 30 4.4 Application of Laplace Transforms to Linear Differential Equations 31 4.4.1 Example: Angle of Radio Telescope 32 4.4.2 Example: Modelling the Angular Velocity of Radio Telescope 33 4.5 A Heuristic Introduction to Laplace Transforms 33 4.6 Transfer Functions 34 4.6.1 High-Order Differential Equation Models 34 4.6.2 Example: Transfer Function for Radio Telescope 35 4.6.3 Transfer Functions for Continuous-Time State-Space Models 35 4.6.4 Example: Inverted Pendulum 36 4.6.5 Poles, Zeros and Other Properties of Transfer Functions 36 4.6.6 Time Delays 36 4.6.7 Heuristic Development of Transfer Function of Delay 37 4.6.8 Example: Heating System 37 4.7 Stability of Transfer Functions 38 4.7.1 Example: Poles of the Radio Telescope Model 38 4.8 Impulse Response of Continuous-Time Linear Systems 38 4.8.1 Impulse Response 38 4.8.2 Convolution and Transfer Functions 39 4.9 Step Response 39 4.10 Steady-State Response and Integral Action 40 4.11 Terms Used to Describe Step Responses 40 4.12 Frequency Response 41 4.12.1 Nyquist Diagrams 43 4.12.2 Bode Diagrams 43 4.12.3 Example: Simple Transfer Function 44 4.13 Revision Questions 45 Further Reading 46 5 Laboratory 1: Modelling of an Electromechanical Servomechanism 47 5.1 Introduction 47 5.2 The Physical Apparatus 47 5.3 Estimation of Motor Parameters 49 5.3.1 Motivation for Building a Model 50 5.3.2 Experiment: Why Build a Model? 50 5.3.3 Step Response Testing 50 5.3.4 Experiment: Measuring the Open-Loop Gain and Time Constant 51 5.3.5 Frequency Response 51 5.3.6 Experiment: Measuring Frequency Response 52 5.3.7 Experiment: Alternative Measurement of Frequency Response 52 5.4 Revision Questions 53 Further Reading 53 Part II Control System Design Techniques for Linear Single-input Single-output Systems 55 6 Analysis of Linear Feedback Systems 57 6.1 Introduction 57 6.2 Feedback Structures 57 6.3 Nominal Sensitivity Functions 59 6.4 Analysing Stability Using the Characteristic Polynomial 60 6.4.1 Example: Pole-Zero Cancellation 61 6.5 Stability and Polynomial Analysis 61 6.5.1 Stability via Evaluation of the Roots 61 6.6 Root Locus (RL) 61 6.7 Nominal Stability Using Frequency Response 63 6.8 Relative Stability: Stability Margins and Sensitivity Peaks 67 6.9 From Polar Plots to Bode Diagrams 68 6.10 Robustness 69 6.10.1 Achieved Sensitivities 69 6.10.2 Robust Stability 69 6.11 Revision Questions 71 Further Reading 72 7 Design of Control Laws for Single-Input Single-Output Linear Systems 73 7.1 Introduction 73 7.2 Closed-Loop Pole Assignment 73 7.2.1 Example: Steam Receiver 74 7.3 Using Root Locus 75 7.3.1 Example: Double Integrator 75 7.3.2 Example: Unstable Process 76 7.4 All Stabilising Control Laws 77 7.5 Design Using the Youla–Kucera Parameterisation 79 7.5.1 Example: Simple First-Order Model 80 7.6 Integral Action 80 7.7 Anti-Windup 81 7.8 PID Design 82 7.8.1 Structure 82 7.8.2 Using the Youla–Kucera Parameterisation for PID Design 84 7.9 Empirical Tuning 84 7.10 Ziegler–Nichols (Z–N) Oscillation Method 84 7.10.1 Example: Third-Order Plant 85 7.11 Two Degrees of Freedom Design 86 7.12 Disturbance Feedforward 86 7.13 Revision Questions 87 Further Reading 88 8 Laboratory 2: Position Control of Electromechanical Servomechanism 89 8.1 Introduction 89 8.2 Proportional Feedback 89 8.2.1 Experiment: Testing a Proportion only Control Law 91 8.3 Using Proportional Plus Derivative Feedback 91 8.3.1 Experiment: Testing a PD Control Law 92 8.4 Tachometer Feedback 92 8.5 PID Design 92 8.5.1 Output Disturbances 92 8.5.2 Input Disturbance 93 8.5.3 A Simple Design Procedure 94 8.5.4 Experiment: Testing a PID Control Law 94 8.6 Revision Questions 95 Further Reading 95 9 Laboratory 3: Continuous Casting Machine: Linear Considerations 97 9.1 Introduction 97 9.2 The Physical Equipment 97 9.3 Modelling of Continuous Casting Machine 99 9.4 Proportional Control 102 9.5 Response to Set-Point Changes 103 9.6 Experiments 103 9.6.1 Experiment: Model Parameter Estimation 103 9.6.2 Low Gain Feedback 104 9.6.3 High Gain Feedback 104 9.7 Effect of Measurement Noise 104 9.7.1 Experiment: Measuring the Impact of Measurement Noise 105 9.8 Pure Integral Control 105 9.8.1 Experiment: Testing Pure Integral Control 106 9.9 PI Control 106 9.9.1 Experiment: Testing PI Control 107 9.9.2 Experiment: Testing the Response to Varying Casting Speed 108 9.10 Feedforward Control 108 9.10.1 Experiment: Testing Feedforward Control 109 9.10.2 Experiment: Testing Sensitivity to the Feedforward Gain 110 9.11 Revision Questions 110 Further Reading 110 10 Laboratory 4: Modelling and Control of Fluid Level in Tanks 113 10.1 Introduction 113 10.2 The Controllers 113 10.3 Physical Modelling 113 10.3.1 Experiment: Estimating Plant Gain and Time Constant 117 10.4 Closed-Loop Level Control for a Single Tank 117 10.4.1 Proportional Only Control 117 10.4.2 Experiment: Testing Proportional Control 117 10.4.3 Integral Only Control 118 10.4.4 Experiment: Testing Integral Control 118 10.4.5 Proportional Plus Integral Control 119 10.4.6 Experiment: Testing PI Control 119 10.4.7 Experiment: Alternative PI Controller 119 10.5 Closed-Loop Level Control of Interconnected Tanks 119 10.6 Revision Questions 120 Further Reading 121 11 Laboratory 5: Wind Power (Mechanical Components) 123 11.1 Introduction 123 11.2 Yaw Control 123 11.2.1 Experiment: Estimating the Yaw Time Constant 127 11.2.2 Design of Yaw Controller 127 11.2.3 Experiment: Testing the Yaw Controller 128 11.3 Rotational Velocity Control 129 11.3.1 Experiment: Testing the Rotational Velocity Control Law 133 11.4 Pitch Control 133 11.5 Experiment: Testing the Pitch Controller 134 11.6 Revision Questions 135 Further Reading 135 Part III More Complex Linear Single-Input Single-Output Systems 137 12 Time Delay Systems 139 12.1 Introduction 139 12.2 Transfer Function Analysis 139 12.3 Classical PID Design Revisited 140 12.4 Padé Approximation 140 12.5 Using the Youla–Kucera Parameterisation 140 12.6 Smith Predictor 141 12.7 Modern Interpretation of Smith Predictor 142 12.8 Sensitivity Trade-Offs 142 12.9 Theoretical Analysis of Effect of Delay Errors on Smith Predictor 143 12.10 Revision Questions 144 Further Reading 145 13 Laboratory 6: Rolling Mill (Transport Delay) 147 13.1 Introduction 147 13.2 The Physical System 147 13.3 Modelling 149 13.3.1 Description of the Process 149 13.3.2 Sensors and Actuators 149 13.3.3 Disturbances 149 13.3.4 Aims of the Control System 149 13.4 Building a Model 150 13.4.1 The Mill Frame 150 13.4.2 Strip Deformation 150 13.4.3 Composite Model 151 13.4.4 Open-Loop Steady-State Performance 152 13.5 Basic Control System Design 152 13.6 Linear Control Ignoring the Time Delay 153 13.6.1 Experiment: Testing a PI Controller 154 13.7 Linear Control Based on Rational Approximation to the Time Delay 155 13.7.1 Experiment: Testing PID Design 156 13.8 Control System Design Based on Smith Predictor 156 13.8.1 Experiment: Testing Smith Predictor 157 13.9 Use of a Soft Sensor 158 13.9.1 The BISRA Gauge 158 13.9.2 Experiment: Testing the BISRA Gauge 159 13.10 Robustness of BISRA Gauge 159 13.10.1 Experiment: Testing Sensitivity to Mill Modulus 159 13.10.2 Experiment: Alternative Solution to Achieve Steady-State Tracking 159 13.11 Revision Questions 159 Further Reading 160 14 Control System Design for Open-Loop Unstable Systems 161 14.1 Introduction 161 14.2 Some Simple Examples of Open-Loop Unstable Systems 161 14.3 All Stabilising Control Laws for Systems Having Undesirable Open-Loop Poles 163 14.4 Revision Questions 164 Further Reading 165 15 Laboratory 7: Control of a Rocket 167 15.1 Introduction 167 15.2 Dynamics of a Rocket in 2D Flight 167 15.2.1 Coordinate Systems 167 15.2.2 Forces 169 15.2.3 Translational Dynamics 170 15.2.4 Rotational Dynamics 170 15.2.5 Composite Model 171 15.3 Equilibrium 171 15.4 Linearised Model 171 15.5 Open-Loop Flight 172 15.6 Controller Design for the Rocket 172 15.6.1 Simplified Design of PID 172 15.6.2 Frequency Domain Design 173 15.7 Experiment: Testing the Control Law 174 15.7.1 Testing the Design Mode in Section 15.6.1 174 15.7.2 Testing the Design Made in Section 15.6.2 175 15.8 Revision Questions 175 Further Reading 175 16 Bode Sensitivity Trade-Offs 177 16.1 Introduction 177 16.2 System Properties 177 16.3 Bode Integral Constraints 178 16.3.1 Open-Loop Stable Systems 178 16.4 Examples of Bode Sensitivity Trade-Offs 178 16.4.1 Open-Loop Unstable Systems 180 16.5 Bode Complementary Sensitivity Integrals 180 16.5.1 Minimum Phase Plants 180 16.5.2 Non-minimum Phase Plants 180 16.6 Bode Sensitivity for Time-Delay Systems 180 16.7 Revision Questions 181 Further Reading 181 Part IV Sampled Data Control Systems 183 17 Principles of Sampled-Data Control System Design 185 17.1 Introduction 185 17.2 A/D Conversion 185 17.3 Sampled Output Noise 185 17.4 D/A Conversion 186 17.5 Sampled-Data Models 187 17.6 Shift Operator Models 187 17.7 Divided Difference Models 187 17.8 Euler Approximate Model 188 17.9 Euler Approximate Model in Delta Domain 188 17.10 Delta Analysis 189 17.11 Historical Notes 189 17.12 An Example of Shift and Delta Models 189 17.13 Sampled-Data Stability 190 17.14 Bode Sensitivity Integrals (Sampled Data Case) 190 17.14.1 Z-Domain 192 17.14.2 Delta Domain 192 17.15 Sampling Zeros 193 17.16 Revision Questions 193 Further Reading 194 18 Laboratory 8: Audio Signal Processing and Optimal Noise Shaping Quantisers 197 18.1 Introduction 197 18.2 The Physical Apparatus 197 18.3 Psychoacoustic Issues 198 18.3.1 Experiment: Testing Your Hearing Sensitivity 199 18.4 Nearest Neighbour Quantisation 200 18.4.1 Experiment: Testing the Nearest Neighbour Quantiser 200 18.5 Optimal Noise Shaping Quantiser 201 18.5.1 Feedback Quantiser 201 18.5.2 Experiment: Test the Feedback Quantiser 202 18.6 Utilising Your Own Hearing Sensitivity 202 18.6.1 Experiment: Test the Feedback Quantiser Using Your Hearing Sensitivity 204 18.7 Audio Quantisation from a Bode Sensitivity Integral Perspective 204 18.7.1 Experiment: Spectrum of Errors 205 18.7.2 Experiment: Testing Bode Sensitivity Integral 205 18.8 Audio Quantisation for More Complex Cases 205 18.8.1 Experiment: More Complex Case 206 18.9 Revision Questions 206 Further Reading 207 Part V Simple Multivariable Control Problems 209 19 Tools Used for Simple Multivariable Control Problems 211 19.1 Introduction 211 19.2 Cascade Control 211 19.2.1 Example of Cascade Control 212 19.3 Imposed SISO Architectures 214 19.4 Relative Gain Array 215 19.5 An Industrial Example 215 19.5.1 The Relative Gain Array 215 19.5.2 A Simple MV Transformation 216 19.6 Revision Questions 216 Further Reading 216 20 Laboratory 9: Wind Power (Electrical Components) 217 20.1 Introduction 217 20.2 Generator Choices 217 20.3 Physical Parameters for the Laboratory Wind Turbine 217 20.4 The Generator and Grid Side Architectures 219 20.5 Background Theory 219 20.5.1 Alpha, Beta Coordinates 220 20.5.2 dq Frame 220 20.5.3 The Inverse Transformation 221 20.5.4 First-Order Dynamics in dq Frame 221 20.6 Generator Side Model 222 20.7 Generator Side Control Law 223 20.7.1 Regulation of I Sd 224 20.7.2 Regulation of I Sq 224 20.7.3 Alignment of dq Frame 224 20.7.4 Conversion of V Sd , V Sq Back to Time Domain 225 20.8 The Link Capacitor Model 225 20.8.1 Current into the Capacitor 225 20.8.2 Dynamics of the Capacitor 225 20.9 Regulation of the Capacitor Voltage 226 20.10 Model for the Grid Side Transformer 226 20.11 The Grid Side Control Law 226 20.11.1 Regulation of I Cq 227 20.11.2 Regulation of I cd 227 20.12 Complete Electrical System Control Law 227 20.13 Testing the Electrical Control Laws 229 20.13.1 Generator Side 229 20.13.2 Grid Side 229 20.14 Experiments on the Complete System 229 20.14.1 Experiment: Testing the Impact of Wind Direction 230 20.14.2 Experiment: Testing the Impact of Wind Speed 231 20.15 Revision Questions 231 Further Reading 233 21 Laboratory 10: Cross-Directional Control in Paper Machines: PID Control 235 21.1 Introduction 235 21.2 Web-Forming Process 235 21.3 Basis Weight Control in a Paper Machine 237 21.4 Process Model 237 21.4.1 Experiment: Measuring the Cross-Directional Profile 241 21.4.2 Experiment: Measuring the Machine Direction Dynamics 241 21.5 Simple SISO Design Ignoring Coupling 241 21.5.1 Experiment: Testing Simple PID Controllers 242 21.6 Simple SISO Design Accounting for Coupling 242 21.6.1 Experiment: Testing a Decoupled PID Structure 243 21.7 Summary 243 21.8 Revision Questions 244 Further Reading 244 Part VI Multivariable Control Systems (More General Methods) 247 22 State Variable Feedback 249 22.1 Introduction 249 22.2 Sampled-Data Control 249 22.2.1 Pole Assignment 249 22.2.2 Linear Quadratic Regulator (LQR) 249 22.3 Dynamic Programming 250 22.4 Infinite Horizon Linear Quadratic Optimal Problem 251 22.5 Delta-Domain Result 251 22.6 Continuous-Time Linear Quadratic Regulator 252 22.6.1 Pole Assignment 252 22.6.2 Continuous-Time Linear Quadratic Regulator 252 22.7 Regulation to a Fixed Set-Point 253 22.8 Frequency Domain Insights into the Linear Quadratic Regulator 254 22.9 Output Feedback 255 22.9.1 A State Estimator (or Observer) 255 22.9.2 Certainty Equivalence 255 22.10 Separation 256 22.11 Achieving Integral Action 256 22.11.1 The Problem 256 22.11.2 The Remedy 256 22.11.3 Properties 257 22.12 All Stabilising Control Laws Revisited 258 22.12.1 Stable Open-Loop Plants 259 22.12.2 Adding Stable Uncontrollable Disturbance States 259 22.12.3 Adding Non-stabilisable Disturbance States 260 22.13 Model Predictive Control 260 22.14 Revision Questions 260 Further Reading 261 23 The Kalman Filter 263 23.1 Introduction 263 23.2 Periodic Disturbances 263 23.2.1 Continuous-Time Model 263 23.2.2 Sampled-Data Process Noise 264 23.2.3 Sampled-Data Measurement Noise 265 23.2.4 The Full Sampled-Data Model 265 23.3 The Best Observer Gain 266 23.4 Steady-State Optimal Estimator 267 23.5 Treating Non-White Noise 268 23.6 Dealing with Constant Disturbances 268 23.7 Periodic Disturbances 268 23.8 Accounting for Delays 269 23.9 Multiple Output Measurements 269 23.10 Continuous-Time Kalman Filter 270 23.11 Linking Continuous Kalman Filter and Discrete Kalman Filter 270 23.12 The Linear Quadratic Regulator Revisited 271 23.13 Quantifying the Performance 271 23.14 Revision Questions 272 Further Reading 274 24 Laboratory 11: Rolling Mill Revisited (Periodic Disturbances) 275 24.1 Introduction 275 24.2 Disturbances 275 24.3 Effects of Roll Eccentricity 276 24.3.1 Experiment: Measuring the Impact of Roll Eccentricity 277 24.4 Tight Feedback Control 277 24.4.1 Experiment: Testing the Impact of Eccentricity on the BISRA Gauge 278 24.4.2 Analysis of the Effect of Control Law Bandwidth 278 24.5 Eccentricity Compensation 278 24.5.1 A Simple Eccentricity Predictor 278 24.6 Optimal Observer Design 279 24.6.1 Experiment: Testing the Eccentricity Estimator 280 24.7 Eccentricity Compensation Using the Kalman Filtering 281 24.7.1 Experiment: Testing the Kalman Filter for Eccentricity Estimation 281 24.8 Conclusion 282 24.9 Revision Questions 282 Further Reading 283 Part VII Introduction to the Modelling and Control of Nonlinear Systems 285 25 Modelling and Analysis of Simple Nonlinear Systems 287 25.1 Introduction 287 25.2 Errors Arising from Large Actuator Movement 287 25.3 Nonlinear Correction by Gain Change 288 25.4 Nonlinear Correction by Cascade Control 288 25.5 Saturation 289 25.5.1 Achieving Integral Action via Feedback 289 25.5.2 Introducing Anti-Windup in Control Laws Implemented via the Youla–Kucera Parameterisation 290 25.5.3 Anti-Windup When an Observer is Used 290 25.6 Extension to Rate Limitations 291 25.7 Minimal Actuator Movement 291 25.8 Describing Function Analysis 291 25.9 Predicting the Period and Amplitude of Oscillations 293 25.10 Revision Questions 293 Further Reading 294 26 Laboratory 12: Continuous Casting Machine (Nonlinear Considerations) 297 26.1 Introduction 297 26.2 The Slide Gate Valve 297 26.3 Investigation of Effect of Nonlinear Valve Geometry 298 26.3.1 Experiment: Testing Impact of the Nonlinear Geometry of the Valve 299 26.3.2 Other Nonlinear Phenomena 300 26.4 An Explanation for the Observed Oscillations 300 26.5 A Redesign to Account for Slip-Stick Friction 302 26.5.1 Experiment: Testing the Impact of Slip-Stick Friction 302 26.6 Revision Questions 303 Further Reading 303 27 Laboratory 13: Cross-Directional Control (Robustness and Impact of Actuator Saturation) 305 27.1 Introduction 305 27.2 Effect of Actuator Saturation Without Anti-Windup Protection 305 27.2.1 Experiment: Impact of Actuator Saturation 305 27.2.2 Experiment: Impact of Actuator Saturation with Decoupled PID Design 306 27.3 PI Decoupled Design with Simple Anti-Windup Protection 306 27.3.1 Experiment: Testing the Simple Anti-Windup Scheme 307 27.4 Conditioning Problems 308 27.4.1 Experiment: Testing Actuator Profile 310 27.5 PI Decoupled Design with Anti-Windup Protection Limited to Low Spatial Frequencies 310 27.5.1 Experiment: Limiting Spatial Frequencies Used in the Controller 310 27.6 PI Decoupled Design with Adaptive Spatial Frequency Selection 311 27.6.1 Experiment: Testing Adaptive Spatial Frequency Selection 312 27.7 Conclusions 312 27.8 Revision Questions 312 Further Reading 312 Part VIII Modelling and Control of More Complex Nonlinear Systems 315 28 Modelling of a Rocket in Three-Dimensional Flight 317 28.1 Introduction 317 28.2 Preliminaries 317 28.2.1 Coordinate Systems 317 28.2.2 Euler Angles in Three Dimensions 318 28.2.3 Time Derivative of Rotation Matrices 320 28.2.4 Angular Velocities 321 28.2.5 Angular Acceleration 321 28.2.6 Cross-Products 323 28.3 Translational Dynamics 323 28.3.1 Forces 323 28.3.2 Model for Translational Dynamics 324 28.4 Rotational Dynamics 324 28.4.1 Torque 324 28.4.2 Model for Rotational Dynamics 325 28.5 Stable or Unstable Rocket 325 28.6 Revision Questions 326 Further Reading 326 29 Modelling of a Steam-Generating Boiler 327 29.1 Introduction 327 29.2 Physical Principles 328 29.2.1 Internal Energy and Enthalpy 328 29.2.2 Ideal Gases 328 29.2.3 Steam 328 29.3 Physical Principles Used in Boiler Modelling 329 29.4 Mass Balances 329 29.5 Constant Volume of Drum, Risers and Downcomers 331 29.5.1 Consequence of Constant Volume of the Drum 332 29.5.2 Consequence of Constant Volume of the Risers 332 29.6 Energy Balances 333 29.6.1 Consequence of Drum Energy Balance 334 29.6.2 Consequences of Energy Balance in the Risers 335 29.7 A Model for Boiler Pressure 335 29.8 A Model for Drum Water Level 336 29.9 Spatial Discretisation and Homogeneous Mixing in the Risers 337 29.9.1 Spatial Discretisation 338 29.9.2 Homogeneous Mixing in a Section of the Risers 339 29.10 Water Flow in the Downcomers 340 29.11 Superheaters 341 29.12 Steam Receiver 341 29.12.1 Mass Balance 342 29.12.2 Energy Balance 342 29.12.3 Constant Volume of the Steam Receiver 342 29.12.4 Summary of the Model for the Steam Receiver 343 29.13 Other Model Components 343 29.13.1 Mass Flow out of Drum 343 29.13.2 Feedwater Mass Flow 344 29.13.3 Total Heat 344 29.13.4 Disturbances 344 29.13.5 A Preliminary Simulation 344 29.14 Revision Questions 344 Further Reading 346 30 Laboratory 14: Control of a Steam Boiler 347 30.1 Introduction 347 30.2 Extracting an Approximate Linear Model 347 30.2.1 Introduction 347 30.2.2 Sine Wave Testing in Closed-Loop (Scalar Case) 348 30.2.3 Application to the Boiler Model 349 30.2.4 The Steam Receiver 350 30.3 The Control Architecture 351 30.4 Regulating Steam Flow from the Boiler 351 30.5 Boiler Pressure Controller 351 30.6 Drum Water Level Controller 352 30.6.1 Experiment: Implementing Drum Water Level Control Law 352 30.7 Steam Receiver Controller 353 30.7.1 Experiment: Testing Steam Receiver Control Law 353 30.8 Experiments 353 30.8.1 Set Up 353 30.8.2 Small Load Change 354 30.8.3 Faster Outer Loop 354 30.8.4 Slower Outer Loop 354 30.8.5 Large Decrease in Load 355 30.8.6 Constraints 355 30.8.7 Large Load Change with ‘Fast’ Outer Loop 355 30.8.8 Large Increase in Load 355 30.9 Summary 355 30.10 Revision Questions 355 Further Reading 356 Index 357

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Book SynopsisDielectric Resonator Antennas A detailed guide to dielectric-based techniques for antenna array design and construction Dielectric designs, which transmit electricity without conducting it, have in recent decades been increasingly incorporated into antenna arrays. The resulting Dielectric Resonator Antennas (DRAs) provide significant benefits over metal antennas, avoiding conduction loss and increasing efficiency. Dielectric elements can also be incorporated into metal antennas to improve performance. Dielectric Resonator Antennas provides an introduction to dielectric-based techniques for manufacturing antenna arrays. It supplies guidelines for identifying dielectric antenna designs (as opposed to metal ones), describes recent developments in dielectric antenna technology, and points toward potential areas of future growth and development. Readers will also find: Cutting-edge DRA applications in microwave and millimeter-wave communications

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Book SynopsisAccelerators for Convolutional Neural Networks Comprehensive and thorough resource exploring different types of convolutional neural networks and complementary accelerators Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. The first part of the book provides an overview of CNNs along with the composit

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Book SynopsisPrinciples of Soft Computing Using Python Programming An accessible guide to the revolutionary techniques of soft computing Soft computing is a computing approach designed to replicate the human mind's unique capacity to integrate uncertainty and imprecision into its reasoning. It is uniquely suited to computing operations where rigid analytical models will fail to account for the variety and ambiguity of possible solutions. As machine learning and artificial intelligence become more and more prominent in the computing landscape, the potential for soft computing techniques to revolutionize computing has never been greater. Principles of Soft Computing Using Python Programming provides readers with the knowledge required to apply soft computing models and techniques to real computational problems. Beginning with a foundational discussion of soft or fuzzy computing and its differences from hard computing, it describes different models for soft computing and

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Book SynopsisA USERS GUIDE TO VACUUM TECHNOLOGY Choose and understand the vacuum technology that fits your project's needs with this indispensable guide Vacuum technology is used to provide process environments for other kinds of engineering technology, making it an unsung cornerstone of hundreds of projects incorporating analysis, research and development, manufacturing, and more. Since it is very often a secondary technology, users primarily interested in processes incorporating it will frequently only encounter vacuum technology when purchasing or troubleshooting. There is an urgent need for a guide to vacuum technology made with these users in mind. For decades, A User's Guide to Vacuum Technology has met this need, with a user-focused introduction to vacuum technology as it is incorporated into semiconductor, optics, solar sell, and other engineering processes. With an emphasis on otherwise neglected subjects and on accessibility to the secondary user of vacuum teTable of ContentsPreface xvii Symbols xix Part I Its Basis 1 1 Vacuum Technology 3 1.1 Units of Measurement 8 References 9 2 Gas Properties 11 2.1 Kinetic Picture of a Gas 11 2.1.1 Velocity Distribution 12 2.1.2 Energy Distribution 13 2.1.3 Mean Free Path 14 2.1.4 Particle Flux 15 2.1.5 Monolayer Formation Time 15 2.1.6 Pressure 16 2.2 Gas Laws 16 2.2.1 Boyle’s Law 17 2.2.2 Amontons’ Law 17 2.2.3 Charles’ Law 18 2.2.4 Dalton’s Law 18 2.2.5 Avogadro’s Law 18 2.2.6 Graham’s Law 19 2.3 Elementary Gas Transport Phenomena 19 2.3.1 Viscosity 19 2.3.2 Thermal Conductivity 22 2.3.3 Diffusion 23 2.3.4 Thermal Transpiration 24 References 25 3 Gas Flow 27 3.1 Flow Regimes 27 3.2 Flow Concepts 29 3.3 Continuum Flow 31 3.3.1 Orifice 32 3.3.2 Long Round Tube 34 3.3.3 Short Round Tube 36 3.4 Molecular Flow 37 3.4.1 Orifice 38 3.4.2 Long Round Tube 39 3.4.3 Short Round Tube 39 3.4.4 Irregular Structures 41 3.4.4.1 Analytical Solutions 42 3.4.4.2 Statistical Solutions 43 3.4.5 Components in Parallel and Series 43 3.5 Models Spanning Molecular and Viscous Flow 53 References 55 4 Gas Release from Solids 59 4.1 Vaporization 59 4.2 Diffusion 60 4.2.1 Reduction of Outdiffusion by Vacuum Baking 62 4.3 Thermal Desorption 63 4.3.1 Zero Order 63 4.3.2 First Order 64 4.3.3 Second Order 65 4.3.4 Desorption from Real Surfaces 67 4.3.5 Outgassing Measurements 67 4.3.6 Outgassing Models 69 4.3.7 Reduction by Baking 69 4.4 Stimulated Desorption 71 4.4.1 Electron-Stimulated Desorption 71 4.4.2 Ion-Stimulated Desorption 71 4.4.3 Stimulated Chemical Reactions 72 4.4.4 Photo Desorption 72 4.5 Permeation 73 4.5.1 Atomic and Molecular Permeation 73 4.5.2 Dissociative Permeation 74 4.5.3 Permeation and Outgassing Units 75 4.6 Pressure Limitations During Pumping 76 References 78 Part II Measurement 81 5 Pressure Gauges 83 5.1 Direct Reading Gauges 83 5.1.1 Diaphragm and Bourdon Gauges 84 5.1.2 Capacitance Manometer 85 5.2 Indirect Reading Gauges 88 5.2.1 Thermal Conductivity Gauges 88 5.2.1.1 Pirani Gauge 90 5.2.1.2 Thermocouple Gauge 91 5.2.1.3 Stability and Calibration 92 5.2.2 Spinning Rotor Gauge 93 5.2.3 Ionization Gauges 95 5.2.3.1 Hot Cathode Gauges 95 5.2.3.2 Hot Cathode Gauge Errors 100 5.2.3.3 Cold Cathode Gauge 103 5.2.3.4 Gauge Calibration 105 References 105 6 Flow Meters 109 6.1 Molar Flow, Mass Flow, and Throughput 109 6.2 Rotameters and Chokes 111 6.3 Differential Pressure Devices 112 6.4 Thermal Mass Flow Technique 114 6.4.1 Mass Flow Meter 114 6.4.2 Mass Flow Controller 117 6.4.3 Mass Flow Meter Calibration 119 References 119 7 Pumping Speed 121 7.1 Definition 121 7.2 Mechanical Pump Speed Measurements 122 7.3 High Vacuum Pump Speed Measurements 123 7.3.1 Methods 123 7.3.2 Gas and Pump Dependence 124 7.3.3 Approximate Speed Measurements 125 7.3.4 Errors 125 References 127 8 Residual Gas Analyzers 129 8.1 Instrument Description 129 8.1.1 Ion Sources 131 8.1.1.1 Open Ion Sources 131 8.1.1.2 Closed Ion Sources 133 8.1.2 Mass Filters 134 8.1.2.1 Magnetic Sector 134 8.1.2.2 RF Quadrupole 135 8.1.2.3 Resolving Power 138 8.1.3 Detectors 138 8.1.3.1 Discrete Dynode Electron Multiplier 139 8.1.3.2 Continuous Dynode Electron Multiplier 140 8.2 Installation and Operation 142 8.2.1 Operation at High Vacuum 142 8.2.1.1 Sensor Mounting 142 8.2.1.2 Stability 143 8.2.2 Operation at Medium and Low Vacuum 145 8.2.2.1 Differentially Pumped Analysis 145 8.2.2.2 Miniature Quadrupoles 148 8.3 Calibration 148 8.4 Choosing an Instrument 149 References 150 9 Interpretation of RGA Data 153 9.1 Cracking Patterns 153 9.1.1 Dissociative Ionization 153 9.1.2 Isotopes 154 9.1.3 Multiple Ionization 154 9.1.4 Combined Effects 154 9.1.5 Ion–Molecule Reactions 157 9.2 Qualitative Analysis 158 9.3 Quantitative Analysis 163 9.3.1 Isolated Spectra 164 9.3.2 Overlapping Spectra 165 References 169 Part III Production 171 10 Mechanical Pumps 173 10.1 Rotary Vane 173 10.2 Lobe 177 10.3 Claw 180 10.4 Multistage Lobe 182 10.5 Scroll 184 10.6 Screw 185 10.7 Diaphragm 185 10.8 Reciprocating Piston 187 10.9 Mechanical Pump Operation 189 References 189 11 Turbomolecular Pumps 191 11.1 Pumping Mechanism 191 11.2 Speed–Compression Relations 192 11.2.1 Maximum Compression 193 11.2.2 Maximum Speed 195 11.2.3 General Relation 197 11.3 Ultimate Pressure 198 11.4 Turbomolecular Pump Designs 199 11.5 Turbo-Drag Pumps 201 References 203 12 Diffusion Pumps 205 12.1 Pumping Mechanism 205 12.2 Speed–Throughput Characteristics 207 12.3 Boiler Heating Effects 211 12.4 Backstreaming, Baffles, and Traps 212 References 215 13 Getter and Ion Pumps 217 13.1 Getter Pumps 217 13.1.1 Titanium Sublimation 218 13.1.2 Non-evaporable Getters 223 13.2 Ion Pumps 224 References 229 14 Cryogenic Pumps 233 14.1 Pumping Mechanisms 234 14.2 Speed, Pressure, and Saturation 237 14.3 Cooling Methods 241 14.4 Cryopump Characteristics 245 14.4.1 Sorption Pumps 246 14.4.2 Gas Refrigerator Pumps 249 14.4.3 Liquid Cryogen Pumps 253 References 253 Part IV Materials 257 15 Materials in Vacuum 259 15.1 Metals 260 15.1.1 Vaporization 260 15.1.2 Permeability 260 15.1.3 Outgassing 261 15.1.3.1 Dissolved Gas 262 15.1.3.2 Surface and Near-Surface Gas 264 15.1.4 Structural Metals 269 15.2 Glasses and Ceramics 272 15.3 Polymers 277 References 281 16 Joints Seals and Valves 285 16.1 Permanent Joints 285 16.1.1 Welding 286 16.1.2 Soldering and Brazing 290 16.1.3 Joining Glasses and Ceramics 291 16.2 Demountable Joints 293 16.2.1 Elastomer Seals 294 16.2.2 Metal Gaskets 300 16.3 Valves and Motion Feedthroughs 302 16.3.1 Small Valves 302 16.3.2 Large Valves 304 16.3.3 Special-Purpose Valves 307 16.3.4 Motion Feedthroughs 308 References 313 17 Pump Fluids and Lubricants 315 17.1 Pump Fluids 315 17.1.1 Fluid Properties 315 17.1.1.1 Vapor Pressure 316 17.1.1.2 Other Characteristics 319 17.1.2 Fluid Types 319 17.1.2.1 Mineral Oils 320 17.1.2.2 Esters 321 17.1.2.3 Silicones 321 17.1.2.4 Ethers 322 17.1.2.5 Fluorochemicals 322 17.1.3 Selecting Fluids 323 17.1.3.1 Rotary, Vane, and Lobe Pump Fluids 323 17.1.3.2 Turbo Pump Fluids 325 17.1.3.3 Diffusion Pump Fluids 325 17.1.4 Reclamation 328 17.2 Lubricants 328 17.2.1 Lubricant Properties 329 17.2.1.1 Absolute Viscosity 330 17.2.1.2 Kinematic Viscosity 331 17.2.1.3 Viscosity Index 332 17.2.2 Selecting Lubricants 333 17.2.2.1 Liquid 333 17.2.2.2 Grease 334 17.2.2.3 Solid Film 336 References 338 Part V Systems 341 18 Rough Vacuum Pumping 343 18.1 Exhaust Rate 344 18.1.1 Pump Size 344 18.1.2 Aerosol Formation 346 18.2 Crossover 350 18.2.1 Minimum Crossover Pressure 351 18.2.2 Maximum Crossover Pressure 354 18.2.2.1 Diffusion 354 18.2.2.2 Turbo 357 18.2.2.3 Cryo 357 18.2.2.4 Sputter-Ion 360 References 362 19 High Vacuum Systems 365 19.1 Diffusion-Pumped Systems 365 19.1.1 Operating Modes 368 19.1.2 Operating Issues 369 19.2 Turbo-Pumped Systems 371 19.2.1 Operating Modes 374 19.2.2 Operating Issues 375 19.3 Sputter-Ion-Pumped Systems 376 19.3.1 Operating Modes 377 19.3.2 Operating Issues 379 19.4 Cryo-Pumped Systems 379 19.4.1 Operating Modes 380 19.4.2 Regeneration 380 19.4.3 Operating Issues 382 19.5 High Vacuum Chambers 383 19.5.1 Managing Water Vapor 384 References 386 20 Ultraclean Vacuum Systems 387 20.1 Ultraclean Pumps 389 20.1.1 Dry Roughing Pumps 390 20.1.2 Turbopumps 390 20.1.3 Cryopumps 390 20.1.4 Sputter-Ion, TSP, and NEG Pumps 391 20.2 Ultraclean Chamber Materials and Components 392 20.3 Ultraclean System Pumping and Pressure Measurement 394 References 398 21 Controlling Contamination in Vacuum Systems 401 21.1 Defining Contamination in a Vacuum Environment 401 21.1.1 Establishing Control of Vacuum Contamination 401 21.1.2 Types of Vacuum Contamination 402 21.1.2.1 Particle Contamination 403 21.1.2.2 Gas Contamination 409 21.1.2.3 Film Contamination 410 21.2 Pump Contamination 411 21.2.1 Low/Rough and Medium Vacuum Pump Contamination 411 21.2.1.1 Fluid-Sealed Mechanical Pumps 412 21.2.1.2 Dry Mechanical Pumps 413 21.2.2 High and UHV Vacuum Pump Contamination 415 21.2.2.1 Diffusion Pumps 416 21.2.2.2 Turbo- and Turbo-Drag Pumps 417 21.2.2.3 Cryopumps 418 21.2.2.4 Sputter-Ion and Titanium-Sublimination Pumps 419 21.3 Evacuation Contamination 420 21.3.1 Particle Sources 420 21.3.2 Remediation Methods 421 21.4 Venting Contamination 422 21.5 Internal Components, Mechanisms, and Bearings 423 21.6 Machining Contamination 426 21.6.1 Cutting, Milling, and Turning 426 21.6.2 Grinding and Polishing 427 21.6.3 Welding 428 21.7 Process-Related Sources 429 21.7.1 Deposition Sources 429 21.7.2 Leak Detection 430 21.8 Lubrication Contamination 432 21.8.1 Liquid Lubricants 432 21.8.2 Solid Lubricants 433 21.8.3 Lamellar, Polymer, and Suspension Lubricants 434 21.9 Vacuum System and Component Cleaning 434 21.9.1 Designing a Cleaning Process 435 21.10 Review of Clean Room Environments for Vacuum Systems 436 21.10.1 The Cleanroom Environment 438 21.10.2 Using Vacuum Systems in a Cleanroom Environment 438 References 442 22 High Flow Systems 445 22.1 Mechanically Pumped Systems 447 22.2 Throttled High Vacuum Systems 449 22.2.1 Chamber Designs 449 22.2.2 Turbo Pumped 451 22.2.3 Cryo Pumped 455 References 459 23 Multichambered Systems 461 23.1 Flexible Substrates 462 23.2 Rigid Substrates 465 23.2.1 Inline Systems 465 23.2.2 Cluster Systems 469 23.3 Analytical Instruments 472 References 472 24 Leak Detection 475 24.1 Mass Spectrometer Leak Detectors 476 24.1.1 Forward Flow 476 24.1.2 Counter flow 477 24.2 Performance 478 24.2.1 Sensitivity 478 24.2.2 Response Time 480 24.2.3 Testing Pressurized Chambers 481 24.2.4 Calibration 482 24.3 Leak Hunting Techniques 483 24.4 Leak Detecting with Hydrogen Tracer Gas 486 References 487 Part VI Appendices 489 Appendix A Units and Constants 491 Appendix B Gas Properties 495 Appendix C Material Properties 509 Appendix D Isotopes 519 Appendix E Cracking Patterns 525 Appendix F Pump Fluid Properties 535 Index 543

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Book SynopsisTackle the most challenging problems in science and engineering with these cutting-edge algorithms Multi-objective optimization problems (MOPs) are those in which more than one objective needs to be optimized simultaneously. As a ubiquitous component of research and engineering projects, these problems are notoriously challenging. In recent years, evolutionary algorithms (EAs) have shown significant promise in their ability to solve MOPs, but challenges remain at the level of large-scale multi-objective optimization problems (LSMOPs), where the number of variables increases and the optimized solution is correspondingly harder to reach. Evolutionary Large-Scale Multi-Objective Optimization and Applications constitutes a systematic overview of EAs and their capacity to tackle LSMOPs. It offers an introduction to both the problem class and the algorithms before delving into some of the cutting-edge algorithms which have been specifically adapted to solving LSMOPs. D

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Book SynopsisHighly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks Next Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies. The scope and depth of this book are balanced for both beginners to advanced users. Additional references are provided for readers who wish to learn more details about certain subjects. Applications of NGMA outside of communications, including data and computing assisted by machine learning, protocol designs, and others, are also covered. Written by four leading experts in the field, Next G

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Book Synopsis

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Book SynopsisCONVERTING POWER INTO CHEMICALS AND FUELS Understand the pivotal role that the petrochemical industry will play in the energy transition by integrating renewable or low-carbon alternatives Power into Chemicals and Fuels stresses the versatility of hydrogen as an enabler of the renewable energy system, an energy vector that can be transported and stored, and a fuel for the transportation sector, heating of buildings and providing heat and feedstock to industry. It can reduce both carbon and local emissions, increase energy security and strengthen the economy, as well as support the deployment of renewable power generation such as wind, solar, nuclear and hydro. With a focus on power-to-X technologies, this book discusses the production of basic petrochemicals in such a way as to minimize the carbon footprint and develop procedures that save energy or use energy from renewable sources. Various different power-to-X system configurations are introduced withTable of ContentsAbout the Book xvii Preface xix Acknowledgments xxiii General Literature xxv Nomenclature xxxi Abbreviations and Acronyms xxxiii 1 Power-to-Chemical Technology 1 1.1 Introduction 2 1.2 Power-to-Chemical Engineering 4 1.2.1 Carbon Dioxide Thermodynamics 4 1.2.2 Carbon Dioxide Aromatization Thermodynamics 12 1.2.3 Reaction Mechanism of Carbon Dioxide Methanation 14 1.2.4 Water Electrolysis Thermodynamics 18 1.2.5 Methane Pyrolysis Reaction Thermodynamic Consideration 20 1.2.5.1 The Carbon-Hydrogen System 20 1.2.6 Reaction Kinetics and Mechanism 27 1.2.7 Thermal Mechanism of Methane Pyrolysis into a Sustainable Hydrogen 28 1.2.8 Catalytic Mechanism Splitting of Methane into a Sustainable Hydrogen 30 1.2.9 Conversion of Methane over Metal Catalysts into a Sustainable Hydrogen 35 1.2.9.1 Nickel Catalysts 35 1.2.9.2 Iron Catalysts 37 1.2.9.3 Regeneration of Metal Catalysts 39 1.2.10 Conversion of Methane over Carbon Catalysts into Clean Hydrogen 40 1.2.10.1 Activity of Carbon Catalysts 40 1.2.10.2 Stability and Deactivation of Carbon Catalysts 42 1.2.10.3 Regeneration of Carbon Catalysts 43 1.2.10.4 Co-Feeding to Extend the Lifetime of Carbon Catalysts 44 1.2.11 Reactors 44 1.2.11.1 Conversion, Selectivity and Yields 44 1.2.11.2 Modelling Approach of the Structured Catalytic Reactors 45 1.2.11.3 Reactor Concept for Catalytic Carbon Dioxide Methanation 46 1.2.11.4 Monolithic Reactors 48 1.2.11.5 Mass Transfer in the Honeycomb and Slurry Bubble Column Reactor 49 1.2.11.6 Heat Transfer in Honeycomb and Slurry Bubble Column Reactors 50 1.2.11.7 Process Design 51 1.2.11.8 Comparison and Outlook 52 1.3 Potential Steps Towards Sustainable Hydrocarbon Technology: Vision and Trends 53 1.3.1 Technology Readiness Levels 54 1.3.2 A Vision for the Oil Refinery of 2030 59 1.3.3 The Transition from Fuels to Chemicals 60 1.3.3.1 Crude Oil to Chemicals Investments 66 1.3.3.2 Available Crude-to-Chemicals Routes 67 1.3.4 Business Trends: Petrochemicals 2025 67 1.3.4.1 Asia-Pacific 69 1.3.4.2 Middle East 70 1.3.4.3 United States 70 1.4 Digital Transformation 71 1.4.1 Benefits of Digital Transformation 71 1.4.2 A New Workforce and Workplace 72 1.4.3 Technology Investment 73 1.4.4 The Greening of the Downstream Industry 74 1.4.4.1 Sustainable Alkylation Technology 75 1.4.4.2 Ecofriendly Catalyst 75 1.5 RAM Modelling 76 1.5.1 RAM1 Site Model 77 1.5.2 RAM2 Plant Models 77 1.5.3 RAM3 Models 78 1.5.4 RAM Modelling Benefit 78 1.6 Conclusions 78 Further Reading 80 2 The Green Shift in Power-to-Chemical Technology and Power-to-Chemical Engineering: A Framework for a Sustainable Future 85 2.1 Introduction 86 2.2 Eco-Friendly Catalyst 87 2.2.1 Development of Catalysts Supported on Carbons for Carbon Dioxide Hydrogenation 88 2.2.2 Properties of Carbon Supports 89 2.3 Hydrogen 91 2.3.1 Different Colours and Costs of Hydrogen 92 2.3.1.1 Blue Hydrogen 92 2.3.1.2 Green Hydrogen 92 2.3.1.3 Grey Hydrogen 93 2.3.1.4 Pink Hydrogen 93 2.3.1.5 Yellow Hydrogen 93 2.3.1.6 Multi-Coloured Hydrogen 93 2.3.1.7 Hydrogen Cost 93 2.4 Alternative Feedstocks 95 2.4.1 Carbon Dioxide-Derived Chemicals 95 2.5 Alternative Power-to-X-Technology 97 2.5.1 Power-to-X-Technology to Produce Electrochemicals and Electrofuels 97 2.6 Partial Oxidation of Methane 99 2.7 Biorefining 99 2.8 Sustainable Production to Advance the Circular Economy 100 2.8.1 Introduction 100 2.8.2 Circular Economy 101 2.8.2.1 Sustainability 101 2.8.2.2 Scope 101 2.8.2.3 Background of the Circular Economy 102 2.8.2.3.1 Emergence of the Idea 102 2.8.2.3.2 Moving Away from the Linear Model 103 2.8.2.3.3 Towards the Circular Economy 103 2.8.3 Circular Business Models 103 2.8.4 Industries Adopting a Circular Economy 104 2.8.4.1 Minimizing Dependence on Fossil Fuels 104 2.8.4.2 Minimizing the Impact of Chemical Synthesis and Manufacturing 105 2.8.4.3 Future Research Needs in Developing a Circular Economy 106 2.9 New Chemical Technologies 106 2.9.1 Renewable Power 107 Further Reading 108 3 Storage Renewable Power-to-Chemicals 113 3.1 Introduction 113 3.2 Terminology 118 3.3 Energy Storage Systems 119 3.4 World Primary Energy Consumption 126 3.4.1 2019 Briefly 126 3.4.2 Energy in 2020 128 3.4.2.1 Not Just Green but Greening 128 3.4.2.2 For Energy, 2020 Was a Year Like No Other 129 3.4.2.3 Glasgow Climate Pact 129 3.4.2.4 Energy in 2020: What Happened and How Surprising Was It 131 3.4.2.5 How Should We Think About These Reductions 131 3.4.2.6 What Can We Learn from the COVID-induced Stress Test 133 3.4.2.7 Progress Since Paris – How Is the World Doing 134 3.5 Carbon Dioxide Emissions 135 3.5.1 Carbon Footprint 136 3.5.1.1 Climate-driven Warming 137 3.5.2 Carbon Emissions in 2020 138 3.6 Clean Fuels ‒ the Advancement to Zero Sulfur 139 3.7 Renewables in 2019 140 3.8 Hydroelectricity and Nuclear Energy 141 3.9 Conclusion 141 Further Reading 142 4 Carbon Capture, Utilization and Storage Technologies 145 4.1 Industrial Sources of Carbon Dioxide 145 4.2 Carbon Capture, Utilization and Storage Technologies 147 4.3 Carbon Dioxide Capture 147 4.4 Developing and Deploying CCUS Technology in the Oil and Gas Industry 155 4.5 Sustainable Steel/Chemicals Production: Capturing the Carbon in the Material Value Chain 158 4.5.1 Valorisation of Steel Mill Gases 158 4.5.2 Summary and Outlook 161 Further Reading 162 5 Integrated Refinery Petrochemical Complexes Including Power-to-X Technologies 165 5.1 Introduction 165 5.2 Synergies Between Refining and Petrochemical Assets 167 5.2.1 Reaching Maximum Added Value – Integrated Refining Schemes 168 5.2.1.1 Fluid Catalytic Cracking Alternates 168 5.2.1.2 Hydrocracking Alternates 170 5.2.2 Comparisons and Sensitivities to Product/Utility Pricing 172 5.2.3 Options for Further Increasing the Petrochemical Value Chain 174 5.3 Carbon Dioxide Emissions 175 5.3.1 Effect of a Carbon Dioxide Tax 176 5.3.2 Crude Oil Effects 179 5.4 Summary 180 5.5 Power- to-X Technology 181 5.6 The Role of Nuclear Power 185 5.6.1 Small Nuclear Power Reactors 187 5.6.2 Conclusion 187 Further Reading 188 6 Power-to-Hydrogen Technology 191 6.1 Introduction 192 6.2 Traditional and Developing Technologies for Hydrogen Production 193 6.3 Dry Reforming of Methane 195 6.4 Tri-reforming of Methane 197 6.5 Greenfield Technology Option → Low Carbon Emission Routes 198 6.5.1 Water Electrolysis 201 6.5.1.1 Alkaline Electrolysis 202 6.5.1.2 Polymer Electrolyte Membrane Electrolysis 203 6.5.1.3 Solid Oxide Electrolysis 204 6.5.2 Methane Pyrolysis 207 6.5.2.1 Process Concepts for Industrial Application 208 6.5.2.2 Perspectives of the Carbon Coproduct 211 6.5.3 Thermochemical Processes 213 6.5.4 Photocatalytic Processes 213 6.5.5 Biomass Electro-Reforming 214 6.5.6 Microorganisms 215 6.5.7 Hydrogen from Other Industrial Processes 215 6.5.8 Hydrogen Production Cost 215 6.5.9 Electrolysers 215 6.5.10 Carbon Footprint 216 6.6 Advances in Chemical Carriers for Hydrogen 216 6.6.1 Demand Drivers 217 6.6.2 Options for Hydrogen Deployment 218 6.6.3 Advances in Hydrogen Storage/Transport Technology 218 6.6.4 Global Supply Chain 220 6.6.5 Power-to-Gas Demo 220 6.6.5.1 Hydrogen Fuelling Stations 221 6.6.5.2 Pathway to Commercialization 221 6.6.5.3 Transportation Studies in North America 221 6.6.6 Future Applications 222 6.7 Ammonia Fuel Cells 223 6.7.1 Proton-Conducting Fuel Cells 223 6.7.2 Polymer Electrolyte Membrane Fuel Cells 224 6.7.3 Proton-conducting Solid Oxide Fuel Cells 224 6.7.4 Alkaline Fuel Cells 225 6.7.5 Direct Ammonia Solid Oxide Fuel Cell 226 6.7.6 Equilibrium Potential and Efficiency of the Ammonia-Fed SOFC 227 6.8 Conclusions 228 Further Reading 228 7 Power-to-Fuels 233 7.1 Introduction 234 7.2 Selection of Fuel Candidates 240 7.2.1 Fuel Production Processes 241 7.3 Power-to-Methane Technology 242 7.3.1 Carbon Dioxide Electrochemical Reduction 242 7.3.2 Carbon Dioxide Hydrogenation 244 7.4 Power-to-Methanol 248 7.5 Power-to-Dimethyl Ether 249 7.6 Chemical Conversion Efficiency 250 7.6.1 Exergy 250 7.6.2 Exergy Efficiency 251 7.6.3 Economic and Environmental Evaluation 251 7.6.4 Fuel Assessment 252 7.6.5 Performance of Fuel Production Processes 253 7.6.6 Process Chain Evaluation 254 7.6.7 Fuel Cost 255 7.7 Well-to-Wheel Greenhouse Gas Emissions 257 7.7.1 Environmental Impact 258 7.7.2 Infrastructure 258 7.7.3 Efficiency 259 7.7.4 Energy/Power Density 259 7.7.5 Pollutant Emissions 260 7.8 Gasoline Electrofuels 260 7.9 Diesel Electrofuels 261 7.10 Electrofuels and/or Electrochemicals 263 7.10.1 Physico-Chemical Properties 264 7.10.1.1 Density 264 7.10.1.2 Tribological Properties 264 7.10.1.3 Combustion Characteristics 265 7.10.1.4 Combustion and Emissions 267 7.10.2 Diesel Engine Efficiency 269 7.10.3 Potential of Diesel Electrofuels 269 7.11 Maturity, TRL, Production and Electrolysis Costs 271 7.11.1 Summary 273 7.12 Power-to-Liquid Technology 274 7.12.1 Power-to-Jet Fuel 275 7.12.2 Power-to-Diesel 276 7.13 Conclusion and Outlook 276 Further Reading 278 8 Power-to-Light Alkenes 283 8.1 Oxidative Dehydrogenation 283 8.1.1 Carbon Dioxide as a Soft Oxidant for Catalytic Dehydrogenation 283 8.1.2 Carbon Dioxide: Oxidative Coupling of Methane 285 8.1.3 From Carbon Dioxide to Lower Olefins 289 8.1.4 Low-Carbon Production of Ethylene and Propylene 291 8.1.4.1 Energy Demand per Unit of Ethylene/Propylene Production via Methanol 292 8.1.4.2 Carbon Dioxide Reduction per Unit of Ethylene/Propylene Production 292 8.1.4.3 Economics of Low-Carbon Ethylene and Propylene Production 293 8.2 Life Cycle Assessment 293 8.2.1 Small-Scale Production of Ethylene 293 8.3 Polymerization Reaction 294 8.3.1 Carbon Dioxide-Based Polymers 294 8.3.1.1 Perspective and Practical Applications 298 Further Reading 299 9 Power-to-BTX Aromatics 301 9.1 Low-Carbon Production of Aromatics 301 9.1.1 Methanol to Aromatics Process 303 9.1.1.1 ZSM-5 Catalyst 304 9.1.1.2 Process Variables 305 9.1.1.3 Kinetic Modelling 306 9.1.1.4 Aromatics via Hydrogen-Based Methanol (TRL7) 307 9.1.1.5 Energy Demand per Unit of Low-Carbon BTX Production 308 9.1.1.6 Carbon Dioxide Reduction 308 9.1.1.7 Economics of Low-Carbon BTX Production 308 9.2 Production of p-Xylene from 2,5-Dimethylfuran and Ethylene 308 9.3 Carbon Dioxide Dehydrogenation of Ethylbenzene to Styrene 309 Further Reading 310 10 Power-to-C 1 Chemicals 313 10.1 Introduction 314 10.2 Carbon Dioxide Utilization into Chemical Technology 317 10.3 Mechanism of Conversion of Carbon Dioxide 318 10.4 Hydrogenation of Carbon Dioxide 319 10.4.1 Heterogeneous Hydrogenation 319 10.4.2 Homogeneous Hydrogenation 323 10.5 Electrochemical Conversion of Carbon Dioxide into Valuable Chemicals 324 10.5.1 Technologies Available for Carbon Dioxide Reduction 325 10.6 Electrochemical Technologies 326 10.6.1 Roles of Ionic Liquids on Electrochemical Carbon Dioxide Reduction Promotion 328 10.6.2 Ionic Liquids as Absorbent for Carbon Dioxide Capture 328 10.6.3 Classification of the Electrode Material 328 10.6.4 High Hydrogen Evolution Overvoltage Metal 329 10.6.5 Low Hydrogen Evolution Overvoltage Metals 329 10.6.6 Copper Electrodes 329 10.6.7 Other Electrodes for Carbon Dioxide Reduction 330 10.7 Power-to-Methanol Technology 331 10.7.1 Carbon Dioxide Electrochemical Reduction 332 10.7.2 Direct Carbon Dioxide Hydrogenation into Methanol 334 10.7.3 Low-Carbon Methanol Production 336 10.7.4 Energy Demand 337 10.8 Power-to-Formic Acid Technology 337 10.8.1 Carbon Dioxide Electrochemical Reduction 338 10.8.2 Carbon Dioxide Hydrogenation 339 10.9 Power-to-Formaldehyde Technology 341 10.9.1 Carbon Dioxide Electrochemical Reduction 342 10.9.2 Carbon Dioxide Hydrogenation 342 10.10 Selective Hydrogenation of Carbon Dioxide to Light Olefins 343 10.10.1 Introduction 343 10.10.2 Carbon Dioxide via FTS to Lower Olefins 345 10.10.3 Methane via FTS to Lower Olefins 347 10.10.4 Carbon Dioxide via FTS to Liquid iso-C 5 -C 13 -Alkanes 349 10.10.4.1 Power-to-Liquids 352 10.10.4.2 Energy Demand per Unit of Synthetic Fuel Production 352 10.10.4.3 Carbon Dioxide Reduction per Unit of Synthetic Fuel Production 353 10.10.4.4 Economics 353 10.10.4.5 Comparison of the Hydrogen-Based Low-Carbon Synthesis Routes 353 10.11 Electrochemical Reduction of Carbon Dioxide to Oxalic Acid 354 10.11.1 Process Design and Modelling 355 10.11.2 Carbon Dioxide Absorption in Propylene Carbonate 356 Further Reading 356 11 Power-to-Green Chemicals 363 11.1 Introduction 364 11.2 Biomethanol Production 365 11.2.1 Biomethanol Production Process 365 11.2.2 Energy and Feedstock Demand per Unit of Biomethanol Production 366 11.2.3 Carbon Dioxide Reduction per Unit of Biomethanol Production 367 11.2.4 Economics of Biomethanol Production 367 11.3 Bioethanol Production 367 11.3.1 Bioethanol Production Process 368 11.3.2 Energy and Feedstock Demand per Unit of Bioethanol Production 369 11.3.3 Carbon Dioxide Reduction per Unit of Bioethanol Production 370 11.3.4 Carbon Dioxide Reduction for (Partially) Replacing Gasoline with Bioethanol 370 11.3.5 Economics of Bioethanol Production 370 11.4 Bioethylene Production 371 11.4.1 Bioethylene Production Process 371 11.4.2 Energy and Feedstock Demand per Unit of Bioethylene Production 371 11.4.3 Carbon Dioxide Reduction per Unit of Bioethylene Production 371 11.4.4 Economics of Bioethylene Production 372 11.5 Biopropylene Production 372 11.5.1 Biopropylene Production Processes 372 11.5.2 Energy and Feedstock Demand per Unit of Biopropylene Production 372 11.5.3 Carbon Dioxide Reduction per Unit of Biopropylene Production 373 11.6 BTX Production from Biomass 373 11.6.1 BTX Production Process 373 11.6.2 Energy and Feedstock Demand per Unit of BTX Production from Biomass 374 11.6.3 Carbon Dioxide Emissions per Unit of BTX Production from Biomass 374 11.7 Comparison of the Biomass-Based Synthesis Routes 374 11.8 Biofuels 376 11.8.1 Biodiesel Production 377 11.8.2 Purification of Glycerol 379 11.8.3 Conversion of Glycerol into Valuable Products 380 11.8.3.1 Solketal Synthesis Process 382 11.8.3.2 Reaction Mechanism 383 11.8.3.3 Kinetics of Reaction 384 11.8.3.4 Catalyst Design 385 11.8.3.5 Batch Process 387 11.8.3.6 Continuous Process 388 11.8.4 Current Issues and Challenges 389 11.8.5 Future Recommendation 391 11.8.6 Conclusion 391 11.9 Higher Alcohols and Ether Biofuels 392 11.9.1 Fuel Production Routes and Sustainability 393 11.9.2 Lignin 394 11.9.3 Fuel Properties 394 11.9.4 Concluding Remarks 396 11.10 Biofuels in the World: Biogasoline and Biodiesel 396 Further Reading 399 12 Industrial Small Reactors 405 12.1 Introduction 405 12.2 Thermochemical Water Splitting 406 12.3 Small Modular Reactors 407 12.4 Nuclear Process Heat for Industry 410 12.4.1 High-temperature Reactors for Process Heat 410 12.4.2 Recovery of Oil from Tar Sands 413 12.4.3 Oil Refining 414 12.4.4 Coal and Its Liquefaction 414 12.4.5 Biomass-Based Ethanol Production 415 12.4.6 District Heating 416 12.5 Microchannel Reduction Cell 416 12.6 Conversion of Carbon Dioxide to Graphene 417 12.7 The Ammonia Synthesis Reactor-Development of Small-scale Plants 419 Further Reading 421 13 Recycling of Waste Plastics → Plastics Circularity 423 13.1 Introduction 424 13.2 Mechanism Aspects of Waste Plastic Pyrolysis 426 13.2.1 Polyethylene and Polypropylene 428 13.2.2 Polyethylene Terephthalate 429 13.2.3 Polyvinyl Chloride 430 13.2.4 Polystyrene 431 13.2.5 Poly (Methyl Methacrylate) 432 13.3 Kinetics 433 13.4 Catalysts 434 13.4.1 Zeolites 434 13.4.2 Fluid Catalytic Cracking Catalysts 434 13.5 Parameters Affecting Pyrolysis 436 13.5.1 Type of Plastic Feed 436 13.5.2 Temperature and Residence Time 437 13.5.3 Pressure 438 13.6 Type of Reactors 438 13.6.1 Rotary Kiln Reactor 438 13.6.2 Screw Feed (Auger) Reactor 439 13.6.3 Fluid Catalytic Cracking Reactor 440 13.6.4 Stirred-Tank Reactor 440 13.6.5 Plasma Pyrolysis Reactor 441 13.6.6 Batch Reactor 442 13.6.7 Fixed Bed Reactor 442 13.6.8 Fluidized Bed Reactor 443 13.6.9 Conical Spouted Bed Reactor 443 13.6.10 Microwave Reactor 444 13.6.11 Pyrolysis in Supercritical Water 445 13.7 Applications of Pyrolysis Products 446 13.7.1 Pyrolysis Gases → Hydrogen and Methane 446 13.7.2 Pyrolysis Oil → Aromatics and Diesel Fuels 446 13.7.3 Pyrolysis Char → Nanotubes 449 Further Reading 450 Index 455

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Book SynopsisNANODEVICES FOR INTEGRATED CIRCUIT DESIGN Nanodevices are an integral part of many of the technologies that we use every day. It is a constantly changing and evolving area, with new materials, processes, and applications coming online almost daily. Increasing demand for smart and intelligent devices in human life with better sensing, communication and signal processing is increasingly pushing researchers and designers towards future design challenges based upon internet-of-things (IoT) applications. Several types of research have been done at the level of solid-state devices, circuits, and materials to optimize system performance with low power consumption. For suitable IoT-based systems, there are some key areas, such as the design of energy storage devices, energy harvesters, novel low power high-speed devices, and circuits. Uses of new materials for different purposes, such as semiconductors, metals, and insulators in different parts of devices, circuits, and energy sources, also plTable of ContentsList of Contributors xiii Preface xvii Acknowledgements xix 1 Growth of Nano-Wire Field Effect Transistor in 21st Century 1Kunal Sinha 1.1 Introduction 2 1.2 Initial Works on Nanowire Field-Effect-Transistors (NW-FET) 3 1.2(A) Theoretical and Simulation Studies on Nanowire FET (NW-FET) 4 1.2(B) Fabrication of Nanowire Field-Effect-Transistor (NW-FET) 10 1.3 Application of Nanowire Field-Effect-Transistors (NW-FET) 15 1.4 Conclusion 17 2 Impact of Silicon Nanowire-Based Transistor in IC Design Perspective 23G. Boopathi Raja 2.1 Introduction 24 2.2 Nanoscale Devices 25 2.3 Nanowire Heterostructures and Silicon Nanowires 29 2.4 Performance Analysis of Si Nanowire with SOI FET 38 2.5 Conclusion 40 3 Kink Effect in Field Effect Transistors: Different Models and Techniques 43Abdelaali Fargi, Sami Ghedira and Adel Kalboussi 3.1 Introduction 44 3.2 Techniques of Kink Effect 45 3.3 Different Models of Kink Effect 48 3.4 Kink Effect in MOS Capacitors 48 3.5 Conclusion 58 4 Next Generation Molybdenum Disulfide FET: Its Properties, Evaluation, and Its Applications 61Vydha Pradeep Kumar and Deepak Kumar Panda 4.1 Introduction of Two-Dimensional Materials 62 4.2 Evaluation of 2D-Materials 64 4.3 Overview of MoS2 66 4.4 Properties of MoS2 68 4.5 Fabrication of MoS2 71 4.6 Applications of MoS2 72 4.7 Comparison of Other 2D Materials with MoS2 75 4.8 Conclusion 80 5 Impact of Working Temperature on the ION /IOFF Ratio of a Hetero Step-Shaped Gate TFET With Improved Ambipolar Conduction 83Bijoy Goswami, Savio Jay Sengupta, Ankur Jyoti Sarmah and Nalin Behari Dev Choudhury 5.1 Introduction 84 5.2 Device Structure 84 5.3 Results and Discussion 86 5.4 Conclusion 89 6 Analysis of RF with DC and@Linearity Parameter and Study of Noise Characteristics of Gate-All-Around Junctionless FET (GAA-JLFET) and Its Applications 93Pratikhya Raut, Umakanta Nanda and Deepak Kumar Panda 6.1 Introduction 94 6.2 Structure of GAA-JLFET 97 6.3 Results and Discussion 98 6.4 Applications 112 6.5 Conclusion 112 7 E-Mode-Operated Advanced III-V Heterostructure Quantum Well Devices for Analog/RF and High-Power Switching Applications 117A. Mohanbabu, N. Vinodhkumar, S. Maheswari, S. Baskaran, V. Janakiraman, M. Saravanan and P. Murugapandiyan 7.1 Silicon Era and Scaling Limit 118 7.2 III-V GaN-Based Compound Semiconductors 119 7.3 Band-Gap Engineering 119 7.4 Quantum Well 120 7.5 Polarization in GaN Devices and their Specific Properties 121 7.6 Strain and Lattice Mismatch in III-N Semiconductors 123 7.7 High Electron Mobility Transistors (HEMTs) 123 7.8 Two-Dimensional Electron Gas (2DEG) 124 7.9 AlGaN/GaN Heterostructure HEMT 125 7.10 Enhancement Mode GaN DH-HEMTs Device With Boron-Doped Gate Cap Layer 129 7.11 High-K Gate Dielectric III-Nitride GaN MIS-HEMT Devices 132 7.12 Conclusion 137 8 Design of FinFET as Biosensor 143Suman Lata Tripathi and Balwinder Raj 8.1 Introduction 143 8.2 Existing FET Based Biosensors 145 8.3 Performance Parameters of Biosensors 149 8.4 FinFET Designed as Biosensor Using Visual TCAD 149 8.5 Biosensors in Disease Detection 152 8.6 Conclusion 153 8.7 Acknowledgement 154 9 Biodegradable and Flexible Electronics: Types and Applications 157Vrinda Gupta, Sachin Himalyan and Archit Sundriyal 9.1 Introduction 158 9.2 Biodegradable and Flexible Electronics 160 9.3 Types of Materials Used for Biodegradable and Flexible Electronics 164 9.4 Applications of Biodegradable and Flexible Electronic Devices 171 9.5 Conclusion 176 10 Novel Parameters Extraction Method of High-Speed PIN Diode for Power Integrated Circuit 181Sami Ghedira and Abdelaali Fargi 10.1 Introduction 182 10.2 Review of the Technology and Physics of Power PIN Diodes 183 10.3 State of the Art of PIN Diode Parameters Extraction 186 10.4 Proposed Method 188 10.5 Validation 205 10.6 Conclusion 207 11 Edge AI -- A Promising Technology 211Remya R., Nalesh S. and Kala S. 11.1 Introduction 211 11.2 Deep Neural Networks 213 11.3 Model Compression Techniques for Deep Learning 216 11.4 Computing Infrastructures 221 11.5 Conclusion 223 12 Tunable Frequency Oscillator 227Abhishek Kumar 12.1 Introduction 227 12.2 Experimental Methods and Materials 230 12.3 Results and Discussion 235 12.4 Conclusion 240 13 Introduction to Nanomagnetic Materials for Electronic Devices: Fundamental, Synthesis, Classification and Applications 243Shivani Malhotra, Mansi Chitkara, Lipika Gupta and Monika Parmar 13.1 Introduction -- An Explanation of the Process and Approach 244 13.2 Nanomaterials 244 13.3 Synthesis and Characterization of Nano Materials 248 13.4 Characterization Technique for Structural Analysis 251 13.5 Magnetic Materials 252 13.6 Classification of Magnetic Materials 253 13.7 Magnetic Properties 256 13.8 Ferrites 258 13.9 Applications of Magnetic Materials 265 13.10 Conclusion 268 References 268 About the Editors 273 Index 275

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Book SynopsisFUTURE FIXED AND MOBILE BROADBAND INTERNET, CLOUDS, AND IoT/AI All-in-one resource on the development of Internet and telecoms worldwide, based on the technological frameworks as defined by the ITU Future Fixed and Mobile Broadband Internet, Clouds, and IoT/AI is a highly comprehensive resource that provides full coverage of existing and future fixed and mobile broadband networks, internet, and telecom and OTT services. This book explains how to perform technical, business, and regulatory analysis for future 5G-Advanced, 6G, WiFi, and optical access. This book also covers optical transport, submarine cable, future satellite broadband, cloud computing, massive and critical IoT and frameworks and use of AI / ML in telecommunications. Topics covered include: Internet technologies, IPv6, QUIC, DNS, IPX, QoS in Internet/IP, cybersecurity, future Internet 2030, Internet governance Future metallic and optica

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Book SynopsisInterconnected Modern Multi-Energy Networks and Intelligent Transportation Systems A timely introduction to the revolutionary technologies reshaping the global energy market The search for more efficient and sustainable ways to meet society's energy requirements has driven recent technological innovation on an unprecedented scale. The energy needs of a growing population coupled with concerns about climate change have posed unique challenges that necessitate novel energy technologies. The transition of modern energy grids towards multi-energy networks, or MENs, promises to be a fundamental transformation in the way we energize our world. Interconnected Modern Multi-Energy Networks and Intelligent Transportation Systems presents an overview of the foundational methodologies and technologies underlying MENs and the groundbreaking vehicle systems that bring them together. With the inclusion of transformative technologies from radically differen

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Book SynopsisSpecialized resource providing detailed coverage of recent advances in theory and applications of sparse arrays Sparse Arrays for Radar, Sonar, and Communications discusses various design approaches of sparse arrays, including those seeking to increase the corresponding one-dimensional and two-dimensional virtual array apertures, as well as others that configure the arrays based on solutions of constrained minimization problems. The latter includes statistical bounds and signal-to-interference and noise ratio; in this respect, the book utilizes the recent strides made in convex optimizations and machine learning for sparse array configurability in both fixed and dynamic environments. Similar ideas are presented for sparse array-waveform design. The book also discusses the role of sparse arrays in improving target detection and resolution in radar, improving channel capacity in massive MIMO, and improving underwater target localization in sonar. It covers different sparse array topologi

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Book SynopsisA comprehensive resource providing basic principles and state-of-the art developments in sensorless control technologies for permanent magnet synchronous machine drives Sensorless Control of Permanent Magnet Synchronous Machine Drives highlights the global research achievements over the last three decades and the sensorless techniques developed by the authors and their colleagues, and covers sensorless control techniques of permanent magnet machines, discussing issues and solutions. Many worked application examples are included to aid in practical understanding of concepts. Written by two pioneering authors in the field, Sensorless Control of Permanent Magnet Synchronous Machine Drives covers sample topics such as: Permanent magnet brushless AC and DC drivesSingle three-phase, dual three-phase, and open winding machinesModern control theory based sensorless methods, covering model reference adaptive system, sliding mode observer, extended Kalman filter, and model predictive controlFlux

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Book SynopsisAn Introduction to Data-Driven Control Systems An introduction to the emerging dominant paradigm in control design Model-based approaches to control systems design have long dominated the control systems design methodologies. However, most models require substantial prior or assumed information regarding the plant's structure and internal dynamics. The data-driven paradigm in control systems design, which has proliferated rapidly in recent decades, requires only observed input-output data from plants, making it more flexible and broadly applicable. An Introduction to Data-Driven Control Systems provides a foundational overview of data-driven control systems methodologies. It presents key concepts and theories in an accessible way, without the need for the complex mathematics typically associated with technical publications in the field, and raises the important issues involved in applying these approaches. The result is a highly readable introduction to wh

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Book SynopsisAPPLYING ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ANALYTICS AND CYBER THREAT DETECTION Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and sys

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Book SynopsisA comprehensive and up-to-date exploration of implementing and managing a security operations center in an open-source environment In Open-Source Security Operations Center (SOC): A Complete Guide to Establishing, Managing, and Maintaining a Modern SOC, a team of veteran cybersecurity practitioners delivers a practical and hands-on discussion of how to set up and operate a security operations center (SOC) in a way that integrates and optimizes existing security procedures. You'll explore how to implement and manage every relevant aspect of cybersecurity, from foundational infrastructure to consumer access points. In the book, the authors explain why industry standards have become necessary and how they have evolved and will evolve to support the growing cybersecurity demands in this space. Readers will also find: A modular design that facilitates use in a variety of classrooms and instructional settings Detailed discussions of SOC tools used for

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Book Synopsis75th Anniversary of the Transistor 75th anniversary commemorative volume reflecting the transistor's development since inception to current state of the art 75th Anniversary of the Transistor is a commemorative anniversary volume to celebrate the invention of the transistor. The anniversary volume was conceived by the IEEE Electron Devices Society (EDS) to provide comprehensive yet compact coverage of the historical perspectives underlying the invention of the transistor and its subsequent evolution into a multitude of integration and manufacturing technologies and applications. The book reflects the transistor's development since inception to the current state of the art that continues to enable scaling to very large-scale integrated circuits of higher functionality and speed. The stages in this evolution covered are in chronological order to reflect historical developments. Narratives and experiences are provided by a select number of venerated industry and academic leaders, an

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Book SynopsisSystems Engineering for the Digital Age Comprehensive resource presenting methods, processes, and tools relating to the digital and model-based transformation from both technical and management views Systems Engineering for the Digital Age: Practitioner Perspectives covers methods and tools that are made possible by the latest developments in computational modeling, descriptive modeling languages, semantic web technologies, and describes how they can be integrated into existing systems engineering practice, how best to manage their use, and how to help train and educate systems engineers of today and the future. This book explains how digital models can be leveraged for enhancing engineering trades, systems risk and maturity, and the design of safe, secure, and resilient systems, providing an update on the methods, processes, and tools to synthesize, analyze, and make decisions in management, mission engineering, and system of systems. Composed of nine chapters, the book covers digitaTable of ContentsList of Contributors xxv Preface xxix Acknowledgment xxxi Acronyms xxxiii About the Companion Website xlv Part I Transforming Engineering Through Digital and Model-Based Methods 1Mark Blackburn 1 Fundamentals of Digital Engineering 3Mark R. Blackburn and Timothy D. West 2 Mission and Systems Engineering Methods 25Benjamin Kruse, Brian Chell, Timothy D. West, and Mark R. Blackburn 3 Transforming Systems Engineering Through Integrating Modeling and Simulation and the Digital Thread 47Daniel Dunbar, Tom Hagedorn, Timothy D. West, Brian Chell, John Dzielski, and Mark R. Blackburn 4 Digital Engineering Visualization Technologies and Techniques 69Brian Chell, Tom Hagedorn, Roger Jones, and Mark R. Blackburn 5 Interactive Model-Centric Systems Engineering 91Donna H. Rhodes and Adam M. Ross Part II Executing Digital Engineering 111Jon Wade 6 Systems Engineering Transformation Through Digital Engineering 113Jon Wade 7 Measuring Systems Engineering Progress Using Digital Engineering 137Tom McDermott, Kaitlin Henderson, Eileen Van Aken, Alejandro Salado, and Joseph Bradley 8 Digital Engineering Implications on Decision-Making Processes 149Samuel Kovacic, Mustafa Canan, Jiang Li, and Andres Sousa-Poza 9 Expedited Systems Engineering for Rapid Capability 175John M. Colombi 10 Scaling Agile Principles to an Enterprise 201Michael Orosz, Brian Duffy, Craig Charlton, Hector Saunders, and Michael Shih 11 System Behavior Specification Verification and Validation (V&V) 219Kristin Giammarco 12 Digital Engineering Transformation: A Case Study 241Cesare Guariniello, Waterloo Tsutsui, Dalia Bekdache, and Dan DeLaurenits Part III Tradespace Analysis in a Digital Engineering Ecosystem -- Context and Implications 267Val Sitterle 13 A Landscape of Trades: The Importance of Process, Ilities, and Practice 269Valerie B. Sitterle and Gary Witus 14 Architecting a Tradespace Analysis Framework in a Digital Engineering Environment 293Daniel Browne, Santiago Balestrini-Robinson, and David Fullmer 15 Set-Based Design: Foundations for Practice 317Shawn Dullen and Dinesh Verma 16 Exploiting Formal Modeling in Resilient System Design: Key Concepts, Current Practice, and Innovative Approach 339Azad M. Madni and Michael Sievers 17 Augmented Intelligence: A Human Productivity and Performance Amplifier in Systems Engineering and Engineered Human--Machine Systems 375Azad M. Madni Part IV Evaluating and Improving System Risk 393Nicole Hutchison 18 Complexity and Risk in Systems Engineering 395Roshanak R. Nilchiani 19 Technical Debt in the Engineering of Complex Systems 419Ye Yang and Dinesh Verma 20 Risk and System Maturity: TRLs and SRLs in Risk Management 435Brian Sauser 21 Managing Risk 463Michael Orosz Part V Model-Based Design of Safety, Security, and Resilience Systems 471Tom McDermott 22 Concepts of Trust and Resilience in Cyber-Physical Systems 473Thomas McDermott, Megan M. Clifford, and Valerie B. Sitterle 23 Introduction to STPA-Sec 489Cody Fleming 24 The "Mission Aware" Concept for Design of Cyber-Resilience 507Peter A. Beling, Megan M. Clifford, Tim Sherburne, Tom McDermott, and Barry M. Horowitz 25 The "FOREST" Concept and Meta-Model for Lifecycle Evaluation of Resilience 523Tim Sherburne, Megan M. Clifford, Barry M. Horowitiz, Tom McDermott, and Peter A. Beling 26 The Cyber Security Requirements Methodology and Meta-Model for Design of Cyber-Resilience 539Tim Sherburne, Megan M. Clifford, Barry M. Horowitz, and Peter A. Beling 27 Implementation Example: Silverfish 555Tim Sherburne, Megan M. Clifford, and Peter A. Beling Part VI Analytic Methods for Design and Analysis of Missions and Systems-of-Systems 581Dan DeLaurenits 28 Unique Challenges in System of Systems Analysis, Architecting, and Engineering 583Judith Dahmann and Dan DeLaurenits 29 System of Systems Analytic Workbench 601Cesare Guariniello, Payuna Uday, Waterloo Tsutsui, and Karen Marais 30 Computational Intelligence Approach to SoS Architecting and Analysis 637Cihan Dagli, Richard Threlkeld, and Lirim Ashiku 31 Unique Challenges in Mission Engineering and Technology Integration 665Michael Orosz, Brian Duffy, Craig Charlton, Hector Saunders, and Ellins Thomas 32 Reference Architecture: An Integration and Interoperability-Driven Framework 683Joel S. Patton and James D. Moreland 33 Mission Engineering Competency Framework 697Gregg Vesonder and Nicole Hutchison Part VII Applying Systems Engineering to Enterprise Systems and Portfolio Management 713Dan DeLaurenits 34 Central Challenges in Modeling and Analyzing Enterprises as Systems 715William B. Rouse 35 Methods for Integrating Dynamic Requirements and Emerging Technologies 729William B. Rouse and Dinesh Verma 36 Portfolio Management and Optimization for System of Systems 747Frank Patterson, David Fullmer, Daniel Browne, and Santiago Balestrini-Robinson 37 Assessing Benefits of Modularity in Missions and System of Systems 775Navindran Davendralingam, Cesare Guariniello, and Lu Xiao Part VIII Systems Education and Competencies in the Age of Digital Engineering, Convergence, and AI 789Nicole Hutchison 38 Using the Systems Engineering Body of Knowledge (SEBoK) 791Nicole Hutchison, Art Pyster, and Rob Cloutier 39 Understanding Critical Skills for Systems Engineers 805Nicole Hutchison 40 Evolving University Programs on Systems Engineering 817Paul T. Grogan 41 Evolving University Programs for the Other 95% of Engineers: A Capstone Marketplace 827William Shepherd Index 843

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