Automatic control engineering Books

Book SynopsisDesign optimization is a standard concept in engineering design, and in other disciplines which utilize mathematical decision-making methods. This textbook focuses on the close relationship between a design problem's mathematical model and the solution-driven methods which optimize it. Along with extensive material on modeling problems, this book also features useful techniques for checking whether a model is suitable for computational treatment. Throughout, key concepts are discussed in the context of why and when a particular algorithm may be successful, and a large number of examples demonstrate the theory or method right after it is presented. This book also contains step-by-step instructions for executing a design optimization project - from building the problem statement to interpreting the computer results. All chapters contain exercises from which instructors can easily build quizzes, and a chapter on 'principles and practice' offers the reader tips and guidance based on the auTrade Review'Principles of Optimal Design, third edition, offers an excellent combination of depth and breadth of fundamentals of mathematical modeling of systems design. Students and practitioners will find the textbook a great starting point to learn about the systems design methods and optimization theories from the fundamentals to the advanced numerical methods. The recent addition of the decomposition-based optimization method and analytical target cascading is a nice expansion to the traditional optimization methods. I use this textbook to teach graduate and advanced undergraduate students who have basic understanding of numerical analysis. Students appreciate the spectrum of contents and they become ready to apply what they learn from the textbook to complex systems design cases. I highly recommend the textbook.' Harrison Hyung, University of Illinois, Urbana-Champaign'Principles of Optimal Design has always been a well-structured textbook that introduces students to the fundamentals of optimal design while remaining accessible and enjoyable to read. The latest edition adds many brief but exciting glimpses of more advanced topics in optimization. These additions have transformed the book from a 'foundation' on which students can firmly stand to a 'catapult' that can propel them to exciting, new, and advanced topics in the broad discipline of optimal design.' Hosam Fathy, Penn State College of Engineering'This third edition brings to the reader an impressive array of new and useful topics in optimal design. For example, and among others, new chapters on non-gradient based methods and decomposition-based optimization (or multi-disciplinary optimization, MDO) have been added. The book can be used both as a textbook for a graduate level course in all engineering fields, but also as a must have reference material. I highly recommend it!' Shapour Azarm, University of Maryland'The Principles of Optimal Design, third edition, is an excellent first text for undergraduates and graduate students alike interested in gaining a firm grasp of practical design optimization methods. It blends the latest modeling techniques with a rigorous treatment of the mathematical analysis, allowing one to adeptly navigate the varied landscapes of modern design problems. From machine learning, automotive systems, financial portfolios, to even the modeling of human purchasing behavior, I have used this text to teach my students how to systematically apply the design process to a broad range of engineering problems.' George J. Delagrammatikas, The Cooper Union for the Advancement of Science and Art, New York'This book, almost thirty years after its first edition, remains the only comprehensive text on engineering design optimization. In our 'one-click' software era, it provides theory fundamentals that tend to be neglected, while complementing them with rigorous modeling and computation techniques. I cannot think of a better textbook for engineering optimization courses, including a plethora of excellent examples and exercises. The third edition is enhanced with new and extremely useful material on recent developments in derivative-free optimization and optimal system design.' Michael Kokkolaras, McGill University, Canada'I've found Principles of Optimal Design to be an excellent, comprehensive explanation of design optimization methods, grounded in rigorous mathematics, yet still accessible. The addition of a gradient-free optimization chapter is a welcome addition to the book.' John Whitefoot, University of Pittsburgh'I've recommended this book to several students. It's a great resource for students who need to use optimization for practical purposes, such as a senior project or an assignment at their co-op job. The book has a good balance between the underlying theory and the application of that theory to actual problems.' Diane Peters, University of MichiganTable of ContentsPreface; Notation; 1. Optimization models; 2. Model construction; 3. Model boundedness; 4. Interior optima; 5. Boundary optima; 6. Local computation; 7. Nongradient search; 8. Systems design; 9. Principles and practice; Notes; References; Author index; Subject index.

Read more less

Book SynopsisTrade Review"Wall Street Journal technology columnist Mims chronicles a product’s journey from manufacturer to doorstep in his timely debut. . . . Readers will be hooked by Mims’s ability to turn what could’ve been a dry supply-chain explainer into a legitimate page-turner. For those interested in what goes on before packages arrive at their door, this is a no-brainer." — Publishers Weekly (starred review) "Mims writes in a digestible style that conveys a pleasing you-are-there quality, and he does not shy away from describing the vast economic inequalities involved in the movement of commodities and the indifference of many managers toward their workers . . . A surprisingly absorbing foray into the optimization of product flow." — Kirkus Reviews "Mims will have readers enthralled with the minutiae of what he calls a 'sophisticated field of human endeavor.' This book will appeal to general audiences and those in any part of the industry." — Booklist "A detailed and dedicated explainer about the state of the logistics industry, Arriving Today by Wall Street Journal tech columnist Christopher Mims offers a snapshot of a logistics industry in flux. The world described in the book is a marvel of human ingenuity . . . a world that, because of the pace of change in the industry, is likely to be unrecognizable in five years’ time." — strategy+business Our global economy runs on logistics. Mims expertly demystifies this secretive science as he vividly portrays the ways in which it often robs the most vulnerable workers of their health and humanity. — Brad Stone, author of The Everything Store and Amazon Unbound With the elegance and efficiency of a first-rate tech journalist, Mims leads us into the nooks and crannies, robots, AI, warehouses, and ships that are highly complex so as to make our daily life simple. A must-read. — Scott Galloway, professor of marketing at NYU Stern School of Business and author of Four and The Algebra of Happiness A meticulously and presciently rendered account of the surprising journey of a USB charger from the factory to my home. It's nice to get your stuff fast. But Mims asks us to ponder, Was it worth it? — Steve LeVine, author of The Powerhouse Adeptly draws us into the container ships, fulfillment centers, and algorithms that deliver us what we want, when we want it. A balanced, much-needed account. — Robert Kanigel, author of The One Best Way and Hearing Homer's Song Mims elegantly explores the micro and the macro of how our modern world of stuff works, in a way that illuminates, dazzles, and sometimes terrifies. — Rose George, author of Ninety Percent of Everything, Nine Pints, and The Big Necessity A backstage pass into the twenty-first-century global economy, Arriving Today is the resource for understanding how modern supply chains really work—and why they sometimes fail. — Ryan Petersen, CEO of Flexport Finally, a book that sheds light on automation, logistics, and their impact on our everyday life today, and in the future. An engaging and insightful narrative. — Oren Etzioni, professor emeritus at the University of Washington and CEO of the Allen Institute for Artificial Intelligence Arriving Today is the essential key to understanding how our world is getting smaller and more interconnected by the day. — Gary Tan, cofounder of Initialized Capital

Read more less

Book SynopsisA futuristic guide to smart structure technologyThrough the use of active controllers, a structure can modify its behavior during dynamic loading such as impact, wind, or earthquake loading. Such structures with self-modification capability are called adaptive or smart structures. Smart structure technology prevents loss of life and damage to structures during natural disasters. This cross-disciplinary book features computational models and algorithms for active control of a new generation of large adaptive structures subjected to various types of dynamic loading. An important focus of the book is the optimization of both the structure and control systems in order to minimize costs.Table of ContentsMicrotasking, Macrotasking, and Autotasking. Formulation of the Integrated Structural/Control Optimization. Parallel Algorithms for Solution of the Eigenvalue Problem. Parallel Algorithms for Solution of the Riccati Equation. Smart Bridge Structures. Smart Multistory Building Structures Under Earthquake and Wind Loadings. Smart Building Structures Under Blast Loading. Simultaneous Optimization of Control System and Structure. Bibliography. Subject Index.

Read more less

Book SynopsisSHORTLISTED FOR THE FINANCIAL TIMES & MCKINSEY 2020 BUSINESS BOOK OF THE YEAROne of Fortune Best Books of the YearOne of Inc. Best Business Books of the YearOne of The Times (UK) Best Business Books of the YearA New York Times Book Review Editors' ChoiceFrom an Oxford economist, a visionary account of how technology will transform the world of work, and what we should do about it From mechanical looms to the combustion engine to the first computers, new technologies have always provoked panic about workers being replaced by machines. For centuries, such fears have been misplaced, and many economists maintain that they remain so today. But as Daniel Susskind demonstrates, this time really is different. Breakthroughs in artificial intelligence mean that all kinds of jobs are increasingly at risk. Drawing on almost a decade of research in the field, Susskind argues that

Read more less

Book Synopsis

Read more less

Book SynopsisThis is an instructional introduction to modern-day industrial process control. The content is both practical and theoretical, with an emphasis on the basic principles and concepts of process control and how they are used in industrial applications.The book is designed to be a self-study course for 2- or 3-year technical or degree students or individuals wishing to expand their knowledge of process control. Each chapter builds on the content of the previous chapter, expanding the reader's understanding of the subject. Example problems are used to illustrate specific concepts, and most chapters contain exercises to test and solidify the reader's understanding of the material. However, each chapter can be considered as a discussion of a specific process control topic. For those who have prior knowledge of process control, each chapter can be read and studied independently or used as a reference of the topic covered. This modular construction also enables educators who wish to incorporate the information into course materials to select specific topics and arrange them in an appropriate sequence to tailor their course material.

Read more less

Book SynopsisThe different chapters of this book cover a large range of information regarding electrical actuators, including: synchronous and asynchronous machine modeling in order to measure and identify offline and online parameters using modern optimization methods; identification in real time of parameters with Luenberger filter and the extended Kalman filter; estimation of non-measurable variables, first by linear estimates and observers, then by lower observers. Robustness is a very problematic issue, as well, which is fully explored in a chapter dedicated to the subject. Finally, the estimate of non-measurable mechanical variables is particularly dealt with: estimate of load moment, then observation of the positioning of a command without mechanical sensor. The conditions to measure variables and real implementation of numerical algorithms are also examined with particular attention.Table of ContentsIntroduction xiii Bernard DE FORNEL and Jean-Paul LOUIS PART I. MEASURES AND IDENTIFICATIONS 1 Chapter 1. Identification of Induction Motor in Sinusoidal Mode 3 Edouard LAROCHE and Jean-Paul LOUIS 1.1. Introduction 3 1.2. The models 4 1.3. Traditional methods from a limited number of measurements 17 1.4. Estimation by minimization of a criteria based on admittance 24 1.5. Linear estimation 36 1.6. Conclusion 44 1.7. Appendix 45 1.8. Bibliography 47 Chapter 2. Modeling and Parameter Determination of the Saturated Synchronous Machine 49 Ernest MATAGNE and Emmanuel DE JAEGER 2.1. Modeling of the synchronous machine: general theory 49 2.2. Classical models and tests 83 2.3. Advanced models: the synchronous machine in saturated mode 100 2.4. Bibliography 116 Chapter 3. Real-Time Estimation of the Induction Machine Parameters 119 Luc LORON 3.1. Introduction 119 3.2. Objectives of parameter estimation 121 3.3. Fundamental problems 124 3.4. Least square methods 138 3.5. Extended Kalman filter 146 3.6. Extended Luenberger observer 158 3.7. Conclusion 168 3.8. Appendix: machine characteristics 169 3.9. Bibliography 169 PART II. OBSERVER EXAMPLES 175 Chapter 4. Linear Estimators and Observers for the Induction Machine (IM) 177 Maria PIETRZAK-DAVID, Bernard DE FORNEL and Alain BOUSCAYROL 4.1. Introduction 177 4.2. Estimation models for the induction machine 178 4.3. Flux estimation 186 4.4. Flux observation190 4.5. Linear stochastic observers—Kalman–Bucy filters 198 4.6. Separate estimation and observation structures of the rotation speed 210 4.7. Adaptive observer 223 4.8. Variable structure mechanical observer (VSMO) 234 4.9. Conclusion 248 4.10. Bibliography 249 Chapter 5. Decomposition of a Determinist Flux Observer for the Induction Machine: Cartesian and Reduced Order Structures 251 Alain BOUSCAYROL, Maria PIETRZAK-DAVID and Bernard DE FORNEL 5.1. Introduction 251 5.2. Estimation models for the induction machine 252 5.3. Cartesian observers 260 5.4. Reduced order observers 271 5.5. Conclusion on Cartesian and reduced order observers 281 5.6. Appendix: parameters of the study induction machine 281 5.7. Bibliography 281 Chapter 6. Observer Gain Determination Based on Parameter Sensitivity Analysis 285 Benoît ROBYNS 6.1. Introduction 285 6.2. Flux observers 286 6.3. Analysis method of the parametric sensitivity 293 6.4. Choice of observer gains 298 6.5. Reduced order flux observer 301 6.6. Full order flux observer 310 6.7. Conclusion 316 6.8. Appendix: parameters of the squirrel-cage induction machine 319 6.9. Bibliography 319 Chapter 7. Observation of the Load Torque of an Electrical Machine 321 Maurice FADEL and Bernard DE FORNEL 7.1. Introduction 321 7.2. Characterization of a load torque relative to an axis of rotation 322 7.3. Modal control of the actuator with load torque observation 330 7.4. Observation of load torque 342 7.5. Robustness of control law by state feedback with observation of the resistant torque 377 7.6. Experimental results 386 7.7. Conclusion 399 7.8. Bibliography 401 Chapter 8. Observation of the Rotor Position to Control the Synchronous Machine without Mechanical Sensor 405 Stéphane CAUX and Maurice FADEL 8.1. State of the art 405 8.2. Reconstruction of the low-resolution position 409 8.3. Exact reconstruction by redundant observer 414 8.4. Exact reconstruction by Kalman filter 436 8.5. Comparison of reconstructions by Kalman filter or analytical redundancy observer 451 8.6. Bibliography 458 List of Authors 461 Index 463

Read more less

Book SynopsisThis book presents the basic tools required to obtain the dynamical models for aerial vehicles (in the Newtonian or Lagrangian approach). Several control laws are presented for mini-helicopters, quadrotors, mini-blimps, flapping-wing aerial vehicles, planes, etc. Finally, this book has two chapters devoted to embedded control systems and Kalman filters applied for aerial vehicles control and navigation. This book presents the state of the art in the area of UAVs. The aerodynamical models of different configurations are presented in detail as well as the control strategies which are validated in experimental platforms.Table of ContentsChapter 1. Aerodynamic Configurations and Dynamic Models 1 Pedro CASTILLO and Alejandro DZUL 1.1. Aerodynamic configurations 1 1.2. Dynamic models 6 1.2.1. Newton-Euler approach 7 1.2.2. Euler-Lagrange approach 9 1.2.3. Quaternion approach 10 1.2.4. Example: dynamic model of a quad-rotor rotorcraft 13 1.3. Bibliography 20 Chapter 2. Nested Saturation Control for Stabilizing the PVTOL Aircraft 21 Isabelle FANTONI and Amparo PALOMINO 2.1. Introduction 21 2.2. Bibliographical study 22 2.3. The PVTOL aircraft model 24 2.4. Control strategy 25 2.4.1. Control of the vertical displacement y 26 2.4.2. Control of the roll angle θ and the horizontal displacement x 27 2.5. Other control strategies for the stabilization of the PVTOL aircraft 33 2.6. Experimental results 33 2.7. Conclusions 38 2.8. Bibliography 38 Chapter 3. Two-Rotor VTOLMini UAV: Design, Modeling and Control 41 Juan ESCARENO, Sergio SALAZAR and Eduardo RONDON 3.1. Introduction 41 3.2. Dynamic model 43 3.2.1. Kinematics 44 3.2.2. Dynamics 44 3.2.3. Model for control analysis 48 3.3. Control strategy 48 3.3.1. Altitude control 49 3.3.2. Horizontal motion control 49 3.3.3. Attitude control 50 3.4. Experimental setup 51 3.4.1. Onboard flight system (OFS) 52 3.4.2. Outboard visual system 53 3.4.3. Experimental results 55 3.5. Concluding remarks 56 3.6. Bibliography 56 Chapter 4. Autonomous Hovering of a Two-Rotor UAV 59 Anand SANCHEZ, Juan ESCARENO and Octavio GARCIA 4.1. Introduction 59 4.2. Two-rotor UAV 60 4.2.1. Description 61 4.2.2. Dynamic model 61 4.3. Control algorithm design 67 4.4. Experimental platform 73 4.4.1. Real-time PC-control system (PCCS) 73 4.4.2. Experimental results 74 4.5. Conclusion 76 4.6. Bibliography 77 Chapter 5. Modeling and Control of a Convertible Plane UAV 79 Octavio GARCIA, Juan ESCARENO and Victor ROSAS 5.1. Introduction 79 5.2. Convertible plane UAV80 5.2.1. Vertical mode 80 5.2.2. Transition maneuver 81 5.2.3. Horizontal mode 81 5.3. Mathematical model 81 5.3.1. Translation of the vehicle 82 5.3.2. Orientation of the vehicle 83 5.3.3. Equations of motion 85 5.4. Controller design 86 5.4.1. Hover control 86 5.4.2. Transition maneuver control 96 5.4.3. Horizontal flight control 102 5.5. Embedded system 106 5.5.1. Experimental platform 106 5.5.2. Microcontroller 108 5.5.3. Inertial measurement unit (IMU) 109 5.5.4. Sensor fusion 109 5.6. Conclusions and future works 111 5.6.1. Conclusions 111 5.6.2. Future works 112 5.7. Bibliography 112 Chapter 6. Control of Different UAVs with Tilting Rotors 115 Juan ESCARENO, Anand SANCHEZ and Octavio GARCIA 6.1. Introduction 115 6.2. Dynamic model of a flying VTOL vehicle 116 6.2.1. Kinematics 117 6.2.2. Dynamics 118 6.3. Attitude control of a flying VTOL vehicle 119 6.4. Triple tilting rotor rotorcraft: Delta 119 6.4.1. Kinetics of Delta 120 6.4.2. Torques acting on the Delta 121 6.4.3. Experimental setup 123 6.4.4. Experimental results 125 6.5. Single tilting rotor rotorcraft: T-Plane 127 6.5.1. Forces and torques acting on the vehicle 127 6.5.2. Experimental results 129 6.6. Concluding remarks 131 6.7. Bibliography 132 Chapter 7. Improving Attitude Stabilization of a Quad-Rotor UsingMotor Current Feedback 133 Anand SANCHEZ, Luis GARCIA-CARRILLO, Eduardo RONDON and Octavio GARCIA 7.1. Introduction 133 7.2. Brushless DC motor and speed controller 134 7.3. Quad-rotor 138 7.3.1. Dynamic model 139 7.4. Control strategy 140 7.4.1. Attitude control 140 7.4.2. Armature current control 142 7.5. System configuration 144 7.5.1. Aerial vehicle 145 7.5.2. Ground station 146 7.5.3. Vision system 147 7.6. Experimental results 148 7.7. Concluding remarks 150 7.8. Bibliography 151 Chapter 8. Robust Control Design Techniques Applied toMini-Rotorcraft UAV: Simulation and Experimental Results 153 José Alfredo GUERRERO, Gerardo ROMERO, Rogelio LOZANO and Efraín ALCORTA 8.1. Introduction 153 8.2. Dynamic model 155 8.3. Problem statement 156 8.4. Robust control design 158 8.5. Simulation and experimental results 160 8.5.1. Simulations 160 8.5.2. Experimental platform 162 8.6. Conclusions 164 8.7. Bibliography 164 Chapter 9. Hover Stabilization of a Quad-Rotor Using a Single Camera 167 Hugo ROMERO and Sergio SALAZAR 9.1. Introduction 167 9.2. Visual servoing 168 9.2.1. Direct visual servoing 169 9.2.2. Indirect visual servoing 169 9.2.3. Position based visual servoing 170 9.2.4. Image-based visual servoing 171 9.2.5.Position-image visual servoing 172 9.3. Camera calibration 173 9.3.1. Two-plane calibration approach 173 9.3.2. Homogenous transformation approach 175 9.4. Pose estimation 177 9.4.1. Perspective of n-points approach 177 9.4.2. Plane-pose-based approach 179 9.5. Dynamic model and control strategy 181 9.6. Platform architecture 183 9.7. Experimental results 184 9.7.1. Camera calibration results 185 9.7.2. Testing phase 185 9.7.3. Real-time results 185 9.8. Discussion and conclusions 186 9.9. Bibliography 188 Chapter 10. Vision-Based Position Control of a Two-Rotor VTOL Mini UAV 191 Eduardo RONDON, Sergio SALAZAR, Juan ESCARENO and Rogelio LOZANO 10.1. Introduction 191 10.2. Position and velocity estimation 193 10.2.1. Inertial sensors 193 10.2.2. Visual sensors 193 10.2.3. Kalman-based sensor fusion 198 10.3. Dynamic model 200 10.4. Control strategy 203 10.4.1. Frontal subsystem (Scamy) 203 10.4.2. Lateral subsystem (Scamx) 204 10.4.3. Heading subsystem (Sψ) 204 10.5. Experimental test bed and results 204 10.5.1. Experimental results 206 10.6. Concluding remarks 207 10.7. Bibliography 207 Chapter 11. Optic Flow-Based Vision System for Autonomous 3D Localization and Control of Small Aerial Vehicles 209 Farid KENDOUL, Isabelle FANTONI and Kenzo NONAMI 11.1. Introduction 209 11.2. Related work and the proposed 3NKF framework 210 11.2.1. Optic flow computation 210 11.2.2.Structure from motion problem 212 11.2.3. Bioinspired vision-based aerial navigation 213 11.2.4. Brief description of the proposed framework 213 11.3. Prediction-based algorithm with adaptive patch for accurate and efficient opticflowcalculation 215 11.3.1. Search center prediction 215 11.3.2. Combined block-matching and differential algorithm 216 11.4. Optic flow interpretation for UAV 3D motion estimation and obstacles detection (SFMproblem) 219 11.4.1. Imaging model 219 11.4.2. Fusion of OF and angular rate data 220 11.4.3. EKF-based algorithm for motion and structure estimation 221 11.5. Aerial platform description and real-time implementation 223 11.5.1. Quadrotor-based aerial platform 223 11.5.2. Real-time software 225 11.6. 3D flight tests and experimental results 227 11.6.1. Experimental methodology and safety procedures 227 11.6.2. Optic flow-based velocity control 227 11.6.3. Optic flow-based position control 229 11.6.4. Fully autonomous indoor flight using optic flow 231 11.7. Conclusion and future work 233 11.8. Bibliography 234 Chapter 12. Real-Time Stabilization of an Eight-Rotor UAV Using Stereo Vision and Optical Flow 237 Hugo ROMERO, Sergio SALAZAR and José GÓMEZ 12.1. Stereo vision 238 12.2. 3D construction 242 12.3. Keypoints matching algorithm 245 12.4. Optical flow-based control 245 12.4.1. Lucas-Kanade approach 247 12.5. Eight-rotorUAV 249 12.5.1. Dynamic model 249 12.5.2. Control strategy 257 12.6. System concept 259 12.7. Real-time experiments 260 12.8. Bibliography 263 Chapter 13. Three-Dimensional Localization 265 Juan Gerardo CASTREJON-LOZANO and Alejandro DZUL 13.1. Kalman filters 266 13.1.1. Linear Kalman filter 266 13.1.2. Extended Kalman filter 269 13.1.3. Unscented Kalman filter 270 13.1.4. Spherical simplex sigma-point Kalman filters 278 13.2. Robot localization 285 13.2.1. Types of localization 285 13.2.2. Inertial navigation theoretical framework 286 13.3. Simulations 289 13.3.1.Quad-rotorhelicopter 289 13.3.2. Inertial navigation simulations 290 13.3.3. Conclusions 296 13.4. Bibliography 297 Chapter 14. Updated Flight Plan for an Autonomous Aircraft in a Windy Environment 301 Yasmina BESTAOUI and Fouzia LAKHLEF 14.1. Introduction 301 14.2. Modeling 304 14.2.1. Down-draftmodeling 304 14.2.2. Translational dynamics 305 14.3. Updated flight planning308 14.3.1. Basic problem statement 310 14.3.2. Hierarchical planning structure 311 14.4. Updates of the reference trajectories: time optimal problem 312 14.5. Analysis of the first set of solutionsS1 315 14.6. Conclusions 323 14.7. Bibliography 323 List of Authors 327 Index 331

Read more less

Book SynopsisSynchronous motors are indubitably the most effective device to drive industrial production systems and robots with precision and rapidity. Their control law is thus critical for combining at the same time high productivity to reduced energy consummation. As far as possible, the control algorithms must exploit the properties of these actuators. Therefore, this work draws on well adapted models resulting from the Park’s transformation, for both the most traditional machines with sinusoidal field distribution and for machines with non-sinusoidal field distribution which are more and more used in industry. Both, conventional control strategies like vector control (either in the synchronous reference frame or in the rotor frame) and advanced control theories like direct control and predictive control are thoroughly presented. In this context, a significant place is reserved to sensorless control which is an important and critical issue in tomorrow’s motors.Table of ContentsIntroduction xv Jean-Paul LOUIS Chapter 1. Synchronous motor controls, Problems and Modeling 1 Jean-Paul LOUIS, Damien FLIELLER, Ngac Ky NGUYEN and Guy STURTZER 1.1. Introduction 1 1.2. Problems on the synchronous motor control 2 1.3. Descriptions and physical modeling of the synchronous motor 6 1.4. Modeling in dynamic regime of the synchronous motor in the natural three-phase a-b-c reference frame 14 1.5. Vector transformations and dynamic models in the α-β and d-q reference frames (sinusoidal field distribution machines with non-salient and salient poles) 24 1.6. Can we extend the Park transformation to synchronous motors with non-sinusoidal field distributions? 31 1.7. Conclusion 39 1.8. Appendices 39 1.9. Bibliography 44 Chapter 2. Optimal Supply and Synchronous Motors Torque Control: Designs in the a-b-c Reference Frame 49 Damien FLIELLER, Jean-Paul LOUIS, Guy STURTZER and Ngac Ky NGUYEN 2.1. Introduction: problems of the controls in a-b-c 49 2.2. Model in the a-b-c reference frame: extension of the steady state approach in transient regime 50 2.3. Structures of torque controls designed in the a-b-c reference frame 54 2.4. Performances and criticisms of the control approach in the a-b-c reference frame 57 2.5. Generalization: extension of the supplies to the case of non-sinusoidal distribution machines 78 2.6. Use of Fourier expansion to obtain optimal currents 90 2.7. Conclusion 112 2.8. Appendices 113 2.9. Bibliography 114 Chapter 3. Optimal Supplies and Synchronous Motors Torque Controls. Design in the d-q Reference Frame 119 Damien FLIELLER, Jean-Paul LOUIS, Guy STURTZER and Ngac Ky NGUYEN 3.1. Introduction: on the controls designed in the Park d-q reference frame 119 3.2. Dynamic model (case of the salient pole machine and constant excitation) 120 3.3. First approach to determine of optimal current references (d-q reference frame)122 3.4. Determination of the current controls designed in the d-q reference frame 124 3.5. New control by model inversion: example of an IP controller with compensations 135 3.6. Optimal supply of the salient poles synchronous motors; geometrical approach of the isotorque curves 143 3.7. Conclusion 166 3.8. Appendices 167 3.9. Bibliography 169 Chapter 4. Drive Controls with Synchronous Motors 173 Jean-Paul LOUIS, Damien FLIELLER, Ngac Ky NGUYEN and Guy STURTZER 4.1. Introduction 173 4.2. Principles adopted for speed controls: case of IP controllers 176 4.3. Speed controls designed in the a-b-c reference frame (application to a non-salient pole machine) 179 4.4. Determination of the speed controls designed in the d-q reference frame (application to a salient pole machine) 184 4.5. Note on position regulations 211 4.6. Conclusion 215 4.7. Appendices 216 4.8. Bibliography 217 Chapter 5. Digital Implementation of Vector Control of Synchronous Motors 221 Flavia KHATOUNIAN and Eric MONMASSON 5.1. Introduction 221 5.2. Classical, analog and ideal torque control of a synchronous motor 223 5.3. Digital implementation problem of the synchronous motor vector control 227 5.4. Discretization of the control system 230 5.5. Study of the delays introduced by the digital implementation of the vector control of the synchronous motor 237 5.6. Quantization problems 241 5.7. Delays in the reverse Park transformation 248 5.8. Conclusion 248 5.9. Bibliography 249 Chapter 6. Direct Control of a Permanent Magnet Synchronous Machine 251 Jean-Marie RÉTIF 6.1. Introduction 251 6.2. Model of the permanent magnet synchronous machine in the d-q reference frame 252 6.3. Conventional DTC with free switching frequency 253 6.4. DTC at a fixed switching frequency 258 6.5. Predictive direct control 264 6.6. Conclusion 279 6.7. Bibliography 280 Chapter 7. Synchronous Machine and Inverter Fault Tolerant Predictive Controls 283 Caroline DOC, Vincent LANFRANCHI and Nicolas PATIN 7.1. Introduction 283 7.2. Topologies of three-phase fault tolerant machines 284 7.3. Topologies of fault tolerant converters 285 7.4. Fault tolerant controls 287 7.5. Conclusion 302 7.6. Bibliography 303 Chapter 8. Characterization of Control without a Mechanical Sensor in Permanent Magnet Synchronous Machines 305 Maurice FADEL 8.1. Introduction 305 8.2. Sensorless control of PMSM, thanks to an extended Kalman filter 313 8.3. Comparison with the MRAS (model reference adaptive system) method 321 8.4. Experimental results comparison 323 8.5. Control without sensor of the PMSM with load torque observation 325 8.6. Starting the PMSM without a mechanical sensor 334 8.7. Conclusion 344 8.8. Bibliography 345 Chapter 9. Sensorless Control of Permanent Magnet Synchronous Machines: Deterministic Methods, Convergence and Robustness 347 Farid MEIBODY-TABAR and Babak NAHID-MOBARAKEH 9.1. Introduction 347 9.2. Modeling PMSMs for mechanical sensorless control 350 9.3. Convergence analysis of mechanical sensorless control laws 356 9.4. Estimation of the back-EMF vector 371 9.5. Robustness of sensorless control of PMSM with respect to parameter uncertainties 373 9.6. Sensorless control of PMSMs in the presence of uncertainties on the resistance 387 9.7. Conclusion 396 9.8. Appendix 1 397 9.9. Appendix 2 397 9.10. Bibliography 398 List of Authors 401 Index 403

Read more less

Book SynopsisMechatronics represents a unifying interdisciplinary and intelligent engineering science paradigm that features an interdisciplinary knowledge area and interactions in terms of the ways of work and thinking, practical experiences, and theoretical knowledge. Mechatronics successfully fuses (but is not limited to) mechanics, electrical, electronics, informatics and intelligent systems, intelligent control systems and advanced modeling, intelligent and autonomous robotic systems, optics, smart materials, actuators and biomedical and biomechanics, energy and sustainable development, systems engineering, artificial intelligence, intelligent computer control, computational intelligence, precision engineering and virtual modeling into a unified framework that enhances the design of products and manufacturing processes. Interdisciplinary Mechatronics concerns mastering a multitude of disciplines, technologies, and their interaction, whereas the science of mechatronics concerns the invention and development of new theories, models, concepts and tools in response to new needs evolving from interacting scientific disciplines. The book includes two sections, the first section includes chapters introducing research advances in mechatronics engineering, and the second section includes chapters that reflects the teaching approaches (theoretical, projects, and laboratories) and curriculum development for under- and postgraduate studies. Mechatronics engineering education focuses on producing engineers who can work in a high-technology environment, emphasize real-world hands-on experience, and engage in challenging problems and complex tasks with initiative, innovation and enthusiasm. Contents: 1. Interdisciplinary Mechatronics Engineering Science and the Evolution of Human Friendly and Adaptive Mechatronics, Maki K. Habib. 2. Micro-Nanomechatronics for Biological Cell Analysis and Assembly, Toshio Fukuda, Masahiro Nakajima, Masaru Takeuchi, Tao Yue and Hirotaka Tajima. 3. Biologically Inspired CPG-Based Locomotion Control System of a Biped Robot Using Nonlinear Oscillators with Phase Resetting, Shinya Aoi. 4. Modeling a Human’s Learning Processes toward Continuous Learning Support System, Tomohiro Yamaguchi, Kouki Takemori and Keiki Takadama. 5. PWM Waveform Generation Using Pulse-Type Hardware Neural Networks, Ken Saito, Minami Takato, Yoshifumi Sekine and Fumio Uchikoba. 6. Parallel Wrists: Limb Types, Singularities and New Perspectives, Raffaele Di Gregorio. 7. A Robot-Assisted Rehabilitation System – RehabRoby, Duygun Erol Barkana and Fatih Özkul. 8. MIMO Actuator Force Control of a Parallel Robot for Ankle Rehabilitation, Andrew Mcdaid, Yun Ho Tsoi and Shengquan Xie. 9. Performance Evaluation of a Probe Climber for Maintaining Wire Rope, Akihisa Tabata, Emiko Hara and Yoshio Aoki. 10. Fundamentals on the Use of Shape Memory Alloys in Soft Robotics, Matteo Cianchetti. 11. Tuned Modified Transpose Jacobian Control of Robotic Systems, S. A. A. Moosavian and M. Karimi. 12. Derivative-Free Nonlinear Kalman Filtering for PMSG Sensorless Control, Gerasimos Rigatos, Pierluigi Siano and Nikolaos Zervos. 13. Construction and Control of Parallel Robots, Moharam Habibnejad Korayem, Soleiman Manteghi and Hami Tourajizadeh. 14. A Localization System for Mobile Robot Using Scanning Laser and Ultrasonic Measurement, Kai Liu, Hongbo Li and Zengqi Sun. 15. Building of Open-Structure Wheel-Based Mobile Robotic Platform, Aleksandar Rodic and Ivan Stojkovic. 16. Design and Physical Implementation of Holonomous Mobile Robot–Holbos, Jasmin Velagic, Admir Kaknjo, Faruk Dautovic, Muhidin Hujdur and Nedim Osmic. 17. Advanced Artificial Vision and Mobile Devices for New Applications in Learning, Entertainment and Cultural Heritage Domains, Gian Luca Foresti, Niki Martinel, Christian Micheloni and Marco Vernier. 18. Application of Stereo Vision and ARM Processor for Motion Control, Moharam Habibnejad Korayem, Michal Irani and Saeed Rafee Nekoo. 19. Mechatronics as Science and Engineering – or Both, Balan Pillai and Vesa Salminen. 20. A Mechatronic Platform for Robotic Educational Activities, Ioannis Kostavelis, Evangelos Boukas, Lazaros Nalpantidis and Antonios Gasteratos. 21. The Importance of Practical Activities in the Formation of Mechatronic Engineers, Joao Carlos M. Carvalho and Vera Lúcia D.S. Franco About the Authors Maki K. Habib is Professor of Robotics and Mechatronics in the School of Science and Engineering, at the American University in Cairo, Egypt. He has been regional editor (Africa/Middle East,) for the International Journal of Mechatronics and Manufacturing Systems (IJMMS) since 2010. He is the recipient of academic awards and has published many articles and books. J. Paulo Davim is Aggregate Professor in the Department of Mechanical Engineering at the University of Aveiro, Portugal and is Head of MACTRIB (Machining and Tribology Research Group). His main research interests include manufacturing, materials and mechanical engineering.Table of ContentsPreface xvii Chapter 1. Interdisciplinary Mechatronics Engineering Science and the Evolution of Human Friendly and Adaptive Mechatronics 1 Maki K. HABIB 1.1. Introduction 2 1.2. Synergetic thinking, learning and innovation in mechatronics design 9 1.3. Human adaptive and friendly mechatronics 11 1.4. Conclusions 14 1.5. Bibliography 15 Chapter 2. Micro-Nanomechatronics for Biological Cell Analysis and Assembly 19 Toshio FUKUDA, Masahiro NAKAJIMA, Masaru TAKEUCHI, Tao YUE and Hirotaka TAJIMA 2.1. Introduction of micro-nanomechatronics on biomedical fields 19 2.2. Configuration of micro-nanomechatronics 21 2.3. Micro-nanomechatronics for single cell analysis 25 2.4. Semi-closed microchip for single cell analysis 28 2.5. Biological cell assembly using photo-linkable resin based on the single cell analysis techniques 30 2.6. Conclusion 33 2.7. Acknowledgments 34 2.8. Bibliography 34 Chapter 3. Biologically Inspired CPG-Based Locomotion Control System of a Biped Robot Using Nonlinear Oscillators with Phase Resetting 37 Shinya AOI 3.1. Introduction 37 3.2. Locomotion control system using nonlinear oscillators 38 3.3. Stability analysis using a simple biped robot model 41 3.4. Experiment using biped robots 58 3.5. Conclusion 64 3.6. Acknowledgments 65 3.7. Bibliography 65 Chapter 4. Modeling a Human’s Learning Processes toward Continuous Learning Support System 69 Tomohiro YAMAGUCHI, Kouki TAKEMORI and Keiki TAKADAMA 4.1. Introduction 70 4.2. Designing the continuous learning by a maze model 76 4.3. The layout design of mazes for the continuous learning task 82 4.3.1. Overview of the continuous learning support system 82 4.3.2. The layout design of mazes on the thinking level space 83 4.4. Experiment 85 4.5. Discussions 88 4.5.1. The role of motivations to drive the continuous learning 88 4.6. Conclusions 92 4.7. Acknowledgments 93 4.8. Bibliography 93 Chapter 5. PWM Waveform Generation Using Pulse-Type Hardware Neural Networks 95 Ken SAITO, Minami TAKATO, Yoshifumi SEKINE and Fumio UCHIKOBA 5.1. Introduction 96 5.2. PWM servo motor 97 5.3. Pulse-type hardware neuron model 99 5.4. Pulse-type hardware neural networks 104 5.5. Measurements of constructed discrete circuit 108 5.6. Conclusion 109 5.7. Acknowledgments 109 5.8. Bibliography 110 Chapter 6. Parallel Wrists: Limb Types, Singularities and New Perspectives 113 Raffaele DI GREGORIO 6.1. Limb architectures and mobility analysis 113 6.2. Singularities and performance indices 124 6.3. New perspectives 139 6.4. Bibliography 142 Chapter 7. A Robot-Assisted Rehabilitation System – RehabRoby 145 Duygun EROL BARKANA and Fatih ÖZKUL 7.1. Introduction 145 7.2. Background 146 7.3. Control architecture 149 7.4. RehabRoby 150 7.5. Controllers of RehabRoby 155 7.6. Concluding remarks 158 7.7. Acknowledgments 159 7.8. Bibliography 159 Chapter 8. MIMO Actuator Force Control of a Parallel Robot for Ankle Rehabilitation 163 Andrew MCDAID, Yun HO TSOI and Shengquan XIE 8.1. Introduction 163 8.2. Ankle rehabilitation robot 167 8.2.1. Design requirements 168 8.3. Actuator force control 176 8.4. Experimental results 198 8.5. Concluding remarks 204 8.6. Bibliography 205 Chapter 9. Performance Evaluation of a Probe Climber for Maintaining Wire Rope 209 Akihisa TABATA, Emiko HARA and Yoshio AOKI 9.1. Introduction 209 9.2. Optimize friction drive conditions using a prototype probe climber 210 9.3. Impact of different surface friction materials for friction pulley made on elevation performance 213 9.4. Damage detection test of elevator wire rope 216 9.5. Damage detection through signal processing 218 9.6. Integrity evaluation of wire rope through MFL strength 219 9.7. Damage detection of wire rope using neural networks 224 9.8. Conclusion 224 9.9. Bibliography 225 Chapter 10. Fundamentals on the Use of Shape Memory Alloys in Soft Robotics 227 Matteo CIANCHETTI 10.1. Introduction 228 10.2. Shape memory effect and superelastic effect 230 10.3. SMA thermomechanical behavior 231 10.4. SMA constitutive models 234 10.5. Hints on SMA thermomechanical testing 235 10.6. Design principles 237 10.7. Fabrication methods 243 10.8. Activation methods and control design 244 10.9. Applications in Soft Robotics 248 10.10. Conclusions 251 10.11. Bibliography 252 Chapter 11. Tuned Modified Transpose Jacobian Control of Robotic Systems 255 S. A. A. MOOSAVIAN and M. KARIMI 11.1. Introduction 256 11.2. TMTJ control law 257 11.3. Obtained results and discussions 265 11.3.1. Fixed base manipulator 265 11.3.2. Mobile base manipulator 269 11.4. Conclusions 272 11.5. Bibliography 273 Chapter 12. Derivative-Free Nonlinear Kalman Filtering for PMSG Sensorless Control 277 Gerasimos RIGATOS, Pierluigi SIANO and Nikolaos ZERVOS 12.1. Introduction 277 12.2. Dynamic model of the permanent magnet synchronous generator 279 12.3. Lie algebra-based design of nonlinear state estimators 282 12.4. Differential flatness for nonlinear dynamical systems 288 12.5. Differential flatness of the PMSG 293 12.6. Robust state estimation-based control of the PMSG 296 12.7. Estimation of PMSG disturbance input with Kalman filtering 298 12.8. Simulation experiments 302 12.9. Conclusions 307 12.10. Bibliography 308 Chapter 13. Construction and Control of Parallel Robots 313 Moharam HABIBNEJAD KORAYEM, Soleiman MANTEGHI and Hami TOURAJIZADEH 13.1. Introduction 313 13.2. A parallel robot mechanism 315 13.3. Actuators 324 13.4. Sensors 328 13.5. Data transfer protocol 342 13.6. Graphical user interface (GUI) 347 13.7. Result and verifications 357 13.8. Conclusion 362 13.9. Bibliography 364 Chapter 14. A Localization System for Mobile Robot Using Scanning Laser and Ultrasonic Measurement 369 Kai LIU, Hongbo LI and Zengqi SUN 14.1. Introduction 369 14.2. System configuration 371 14.3. Implementation 373 14.4. Experimental results 377 14.5. Conclusion 382 14.6. Acknowledgments 383 14.7. Bibliography 383 Chapter 15. Building of Open-Structure Wheel-Based Mobile Robotic Platform 385 Aleksandar RODIÆ and Ivan STOJKOVIÆ 15.1. Introduction 385 15.2. State of the art 386 15.3. Configuring of the experimental system 389 15.4. Modeling and simulation of the system 394 15.5. Motion planning and control 403 15.6. Simulation and experimental testing 409 15.7. Concluding remarks 416 15.8. Acknowledgments 417 15.9. Bibliography 417 15.10. Appendix 421 Chapter 16. Design and Physical Implementation of Holonomous Mobile Robot – Holbos 423 Jasmin VELAGIC, Admir KAKNJO, Faruk DAUTOVIC, Muhidin HUJDUR and Nedim OSMIC 16.1. Introduction 423 16.2. Locomotion of holonomous mobile robot 424 16.3. Mechanical design 430 16.4. Electrical design 431 16.5. Results 444 16.6. Conclusion 447 16.7. Bibliography 448 Chapter 17. Advanced Artificial Vision and Mobile Devices for New Applications in Learning, Entertainment and Cultural Heritage Domains 451 Gian Luca FORESTI, Niki MARTINEL, Christian MICHELONI and MARCO VERNIER 17.1. Introduction 451 17.2. Chapter contributions 455 17.3. Mobile devices for education purposes 456 17.4. Image processing supports HCI in museum application 461 17.5. Back to the Future: a 3D image gallery 471 17.6. Conclusions and future works 477 17.7. Bibliography 477 Chapter 18. Application of Stereo Vision and ARM Processor for Motion Control 483 Moharam HABIBNEJAD KORAYEM, Michal IRANI and Saeed RAFEE NEKOO 18.1. Introduction 483 18.2. Stereo vision 486 18.3. Triangulation 487 18.4. End-effector orientation 490 18.5. Experimental setup and results 492 18.6. Summary 497 18.7. Bibliography 498 Chapter 19. Mechatronics as Science and Engineering – or Both 501 Balan PILLAI and Vesa SALMINEN 19.1. Introduction 501 19.2. Theories and methods of design, planning and manufacturing 504 19.3. Complexity versus complicatedness 506 19.4. Benefits of fast product developments 513 19.5. Nature of product development process 516 19.6. Planning the timetable of a product design project 518 19.7. Designing the product concept 520 19.8. Enhancing conceptual design 520 19.9. Interaction between the parts of the machine 523 19.10. Effect of the strength of interaction between product parts and development speed 524 19.11. Definition of product and service 527 19.12. The case studies 529 19.13. Networking systems and learning mechanism 531 19.14. Model-based methodology: an implemented case 536 19.15. Conclusions 540 19.16. Bibliography 541 Chapter 20. A Mechatronic Platform for Robotic Educational Activities 543 Ioannis KOSTAVELIS, Evangelos BOUKAS, Lazaros NALPANTIDIS and Antonios GASTERATOS 20.1. Introduction 543 20.2. System overview 545 20.3. Educational activities 554 20.4. Experiences from educational activities 561 20.5. Conclusions 565 20.6. Acknowledgments 565 20.7. Bibliography 566 Chapter 21. The Importance of Practical Activities in the Formation of Mechatronic Engineers 569 João Carlos M. CARVALHO and Vera Lúcia D.S. FRANCO 21.1. Introduction 569 21.2. Curricular and extracurricular practical activities 575 21.3. Undergraduate course of Mechatronics Engineering at the Federal University of Uberlândia/Brazil 580 21.4. Discussions 588 21.5. Conclusions 590 21.6. Bibliography 591 List of Authors 593 Index 599

Read more less

Book SynopsisThe purpose of this book is to present the main methods of static and dynamic optimization. It has been written within the framework of the European Union project – ERRIC (Empowering Romanian Research on Intelligent Information Technologies), funded by the EU’s FP7 Research Potential program and developed in cooperation between French and Romanian teaching researchers. Through the principles of various proposed algorithms (with additional references) this book allows the interested reader to explore various methods of implementation such as linear programming, nonlinear programming – particularly important given the wide variety of existing algorithms, dynamic programming with various application examples and Hopfield networks. The book examines optimization in relation to systems identification; optimization of dynamic systems with particular application to process control; optimization of large scale and complex systems; optimization and information systems.Table of ContentsForeword ix Preface xi List of Acronyms xiii Chapter 1. Linear Programming 1 1.1. Objective of linear programming 1 1.2. Stating the problem 1 1.3. Lagrange method 4 1.4. Simplex algorithm 5 1.4.1. Principle 5 1.4.2. Simplicial form formulation 5 1.4.3. Transition from one simplicial form to another 7 1.4.4. Summary of the simplex algorithm 9 1.5. Implementation example 11 1.6. Linear programming applied to the optimization of resource allocation 13 1.6.1. Areas of application 13 1.6.2. Resource allocation for advertising 13 1.6.3. Optimization of a cut of paper rolls 16 1.6.4. Structure of linear program of an optimal control problem 17 Chapter 2. Nonlinear Programming 23 2.1. Problem formulation 23 2.2. Karush–Kuhn–Tucker conditions 24 2.3. General search algorithm 26 2.3.1. Main steps 26 2.3.2. Computing the search direction 29 2.3.3. Computation of advancement step 33 2.4. Monovariable methods 33 2.4.1. Coggin’s method (of polynomial interpolation) 34 2.4.2. Golden section method 36 2.5. Multivariable methods 39 2.5.1. Direct search methods 39 2.5.2. Gradient methods 57 Chapter 3. Dynamic Programming 101 3.1. Principle of dynamic programming 101 3.1.1. Stating the problem 101 3.1.2. Decision problem 101 3.2. Recurrence equation of optimality 102 3.3. Particular cases 104 3.3.1. Infinite horizon stationary problems 104 3.3.2. Variable horizon problem 104 3.3.3. Random horizon problem 104 3.3.4. Taking into account sum-like constraints 105 3.3.5. Random evolution law 106 3.3.6. Initialization when the final state is imposed 106 3.3.7. The case when the necessary information is not always available 107 3.4. Examples 107 3.4.1. Route optimization 107 3.4.2. The smuggler problem 109 Chapter 4. Hopfield Networks 115 4.1. Structure 115 4.2. Continuous dynamic Hopfield networks 117 4.2.1. General problem 117 4.2.2. Application to the traveling salesman problem 121 4.3. Optimization by Hopfield networks, based on simulated annealing 123 4.3.1. Deterministic method 123 4.3.2. Stochastic method 125 Chapter 5. Optimization in System Identification 131 5.1. The optimal identification principle 131 5.2. Formulation of optimal identification problems 132 5.2.1. General problem 132 5.2.2. Formulation based on optimization theory 133 5.2.3. Formulation based on estimation theory (statistics) 136 5.3. Usual identification models 138 5.3.1. General model 138 5.3.2. Rational input/output (RIO) models 140 5.3.3. Class of autoregressive models (ARMAX) 142 5.3.4. Class of state space representation models 145 5.4. Basic least squares method 146 5.4.1. LSM type solution 146 5.4.2. Geometric interpretation of the LSM solution 151 5.4.3. Consistency of the LSM type solution 154 5.4.4. Example of application of the LSM for an ARX model 157 5.5. Modified least squares methods 158 5.5.1. Recovering lost consistency 158 5.5.2. Extended LSM 162 5.5.3. Instrumental variables method 164 5.6. Minimum prediction error method 168 5.6.1. Basic principle and algorithm 168 5.6.2. Implementation of the MPEM for ARMAX models 171 5.6.3. Convergence and consistency of MPEM type estimations 174 5.7. Adaptive optimal identification methods 175 5.7.1. Accuracy/adaptability paradigm 175 5.7.2. Basic adaptive version of the LSM 177 5.7.3. Basic adaptive version of the IVM 182 5.7.4. Adaptive window versions of the LSM and IVM 183 Chapter 6. Optimization of Dynamic Systems 191 6.1. Variational methods 191 6.1.1. Variation of a functional 191 6.1.2. Constraint-free minimization 192 6.1.3. Hamilton canonical equations 194 6.1.4. Second-order conditions 195 6.1.5. Minimization with constraints 195 6.2. Application to the optimal command of a continuous process, maximum principle 196 6.2.1. Formulation 196 6.2.2. Examples of implementation 198 6.3. Maximum principle, discrete case 206 6.4. Principle of optimal command based on quadratic criteria 207 6.5. Design of the LQ command 210 6.5.1. Finite horizon LQ command 210 6.5.2. The infinite horizon QL command 217 6.5.3. Robustness of the LQ command 221 6.6. Optimal filtering 224 6.6.1. Kalman–Bucy predictor 225 6.6.2. Kalman–Bucy filter 231 6.6.3. Stability of Kalman–Bucy estimators 234 6.6.4. Robustness of Kalman–Bucy estimators 235 6.7. Design of the LQG command 239 6.8. Optimization problems connected to quadratic linear criteria 245 6.8.1. Optimal control by state feedback 245 6.8.2. Quadratic stabilization 248 6.8.3. Optimal command based on output feedback 249 Chapter 7. Optimization of Large-Scale Systems 251 7.1. Characteristics of complex optimization problems 251 7.2. Decomposition techniques 252 7.2.1. Problems with block-diagonal structure 253 7.2.2. Problems with separable criteria and constraints 267 7.3. Penalization techniques 283 7.3.1. External penalization technique 284 7.3.2. Internal penalization technique 285 7.3.3. Extended penalization technique 286 Chapter 8. Optimization and Information Systems 289 8.1. Introduction 289 8.2. Factors influencing the construction of IT systems 290 8.3. Approaches 292 8.4. Selection of computing tools 296 8.5. Difficulties in implementation and use 297 8.6. Evaluation 297 8.7. Conclusions 298 Bibliography 299 Index 307

Read more less

Book SynopsisReverse Engineering in Control Design proposes practical approaches to building a standard H-infinity problem taking into account an initial controller. Such approaches allow us to mix various control objectives and to initialize procedures for a fixed-structure controller design. They are based on the Observer-Based Realization (OBR) of controllers. The interest of OBR from the controller implementation point of view is detailed and highlighted in this book through academic examples. An open-source toolbox is available to implement these approaches in Matlab®. Throughout the book academic applications are proposed to illustrate the various basic principles. These applications have been chosen by the author for their pedagogic contents and demo files and embedded Matlab® functions can be downloaded so readers can run these illustrations on their personal computers. Contents 1. Observer-based Realization of a Given Controller. 2. Cross Standard Form and Reverse Engineering. 3. Reverse Engineering for Mechanical Systems. Appendix 1. A Preliminary Methodological Example. Appendix 2. Discrete-time Case. Appendix 3. Nominal State-feedback for Mechanical Systems. Appendix 4. Help of Matlab® Functions. About the Authors Daniel Alazard is Professor in System Dynamics and Control at Institut Supérieur de l'Aéronautique et de l’Espace (ISAE), Toulouse, France – SUPAERO Graduate Program. His main research interests concern robust control, flexible structure control and their applications to various aerospace systems.Table of ContentsNOMENCLATURE ix INTRODUCTION xi CHAPTER 1. OBSERVER-BASED REALIZATION OF A GIVEN CONTROLLER 1 1.1. Introduction 1 1.2. Principle 3 1.3. A first illustration 9 1.4. Augmented-order controllers 12 1.5. Discussion 16 1.6. In brief 19 1.7. Reduced-order controllers case 20 1.8. Illustrations 23 1.8.1. Illustration 1: plant state monitoring 24 1.8.2. Illustration 2: controller switching 26 1.8.3. Illustration 3: smooth gain scheduling 29 1.9. Reference inputs in observer-based realizations 31 1.9.1. General results 31 1.9.2. Illustration 33 1.10. Disturbance monitoring and rejection 36 1.10.1. General results 36 1.10.2. Illustration 40 1.11. Minimal parametric description of a linear system 44 1.12. Selection of the observer-based realization 47 1.12.1. Luenberger observer dynamics assignment 47 1.12.2. State-estimator dynamics assignment 48 1.13. Conclusions 49 1.14. Bibliography 49 CHAPTER 2. CROSS STANDARD FORM AND REVERSE ENGINEERING 53 2.1. Introduction 53 2.2. Definitions 55 2.3. Low-order controller case (nK ≤ n) 56 2.3.1. Uniqueness condition 58 2.3.2. Existence of a CSF 59 2.4. Augmented-order controller case (nK > n) 61 2.5. Illustration 61 2.5.1. Solving the inverse H∞-optimal control problem 61 2.5.2. Improving K0 with frequency-domain specification 64 2.5.3. Improving K0 with phase lead 66 2.6. Pseudo-cross standard form 69 2.6.1. A reference model tracking problem 69 2.6.2. Illustration 70 2.6.3. Comment 72 2.7. Conclusions 72 2.8. Bibliography 73 CHAPTER 3. REVERSE ENGINEERING FOR MECHANICAL SYSTEMS 77 3.1. Introduction 77 3.2. Context 78 3.3. Model, specifications and initial controller 79 3.4. H∞ design based on the acceleration sensitivity function 81 3.4.1. General results 81 3.4.2. Illustration 84 3.4.3. Analysis on an augmented model 88 3.4.4. Illustration 88 3.4.5. Synthesis on an augmented model 89 3.4.6. Illustration 91 3.4.7. Taking into account a roll-off specification 94 3.4.8. Illustration 96 3.4.9. Taking into account an integral term 98 3.4.10. Illustration 100 3.5. Mixed H2/H∞ design based on the acceleration sensitivity function 102 3.5.1. The one degree of freedom case 103 3.5.2. First-order optimality conditions 106 3.5.3. Numerical solution using Matlab® 118 3.5.4. Multi-variable case 120 3.6. Aircraft lateral flight control design 121 3.6.1. Model and specifications 121 3.6.2. Basic H2/H∞ control problem 123 3.6.3. Augmented H∞ control problem 126 3.7. Conclusions 130 3.8. Bibliography 131 CONCLUSIONS AND PERSPECTIVES 135 APPENDICES 139 Appendix 1. A Preliminary Methodological Example 141 Appendix 2. Discrete-time Case 149 Appendix 3. Nominal State-feedback for Mechanical Systems 153 Appendix 4. Help of Matlab® Functions 159 LIST OF FIGURES 169 INDEX 175

Read more less

Book SynopsisThe classic approach in Automatic Control relies on the use of simplified models of the systems and reformulations of the specifications. In this framework, the control law can be computed using deterministic algorithms. However, this approach fails when the system is too complex for its model to be sufficiently simplified, when the designer has many constraints to take into account, or when the goal is not only to design a control but also to optimize it. This book presents a new trend in Automatic Control with the use of metaheuristic algorithms. These kinds of algorithm can optimize any criterion and constraint, and therefore do not need such simplifications and reformulations. The first chapter outlines the author’s main motivations for the approach which he proposes, and presents the advantages which it offers. In Chapter 2, he deals with the problem of system identification. The third and fourth chapters are the core of the book where the design and optimization of control law, using the metaheuristic method (particle swarm optimization), is given. The proposed approach is presented along with real-life experiments, proving the efficiency of the methodology. Finally, in Chapter 5, the author proposes solving the problem of predictive control of hybrid systems. Contents 1. Introduction and Motivations. 2. Symbolic Regression. 3. PID Design Using Particle Swarm Optimization. 4. Tuning and Optimization of H-infinity Control Laws. 5. Predictive Control of Hybrid Systems. About the Authors Guillaume Sandou is Professor in the Automatic Department of Supélec, in Gif Sur Yvette, France. He has had 12 books, 8 journal papers and 1 patent published, and has written papers for 32 international conferences.His main research interests include modeling, optimization and control of industrial systems; optimization and metaheuristics for Automatic Control; and constrained control.Table of ContentsPREFACE ix CHAPTER 1. INTRODUCTION AND MOTIVATIONS 1 1.1. Introduction: automatic control and optimization 1 1.2. Motivations to use metaheuristic algorithms 3 1.3. Organization of the book 5 CHAPTER 2. SYMBOLIC REGRESSION 7 2.1. Identification problematic and brief state of the art 7 2.2. Problem statement and modeling 10 2.2.1. Problem statement 10 2.2.2. Problem modeling 10 2.3. Ant colony optimization 13 2.3.1. Ant colony social behavior 13 2.3.2. Ant colony optimization 14 2.3.3. Ant colony for the identification of nonlinear functions with unknown structure 16 2.4. Numerical results 18 2.4.1. Parameter settings 18 2.4.2. Experimental results 19 2.5. Discussion 22 2.5.1. Considering real variables 22 2.5.2. Local minima 22 2.5.3. Identification of nonlinear dynamical systems 23 2.6. A note on genetic algorithms for symbolic regression 23 2.7. Conclusions 25 CHAPTER 3. PID DESIGN USING PARTICLE SWARM OPTIMIZATION 27 3.1. Introduction 27 3.2. Controller tuning: a hard optimization problem 29 3.2.1. Problem framework 29 3.2.2. Expressions of time domain specifications 30 3.2.3. Expressions of frequency domain specifications 32 3.2.4. Analysis of the optimization problem 35 3.3. Particle swarm optimization implementation 35 3.4. PID tuning optimization 37 3.4.1. Case study: magnetic levitation 37 3.4.2. Time response optimization 39 3.4.3. Time response optimization with penalization on the control input 41 3.4.4. Time response optimization with penalization on the control input and constraint on module margin 42 3.5. PID multiobjective optimization 43 3.6. Conclusions 48 CHAPTER 4. TUNING AND OPTIMIZATION OF H∞ CONTROL LAWS 51 4.1. Introduction 51 4.2. H∞ synthesis 54 4.2.1. Full-order H∞ synthesis 54 4.2.2. Tuning the filters as an optimization problem 57 4.2.3. Reduced-order H∞ synthesis 58 4.3. Application to the control of a pendulum in the cart 60 4.3.1. Case study 60 4.3.2. H∞ synthesis schemes 64 4.3.3. Optimization of the parameters of the filters 66 4.3.4. Reduced-order H∞ synthesis: one DOF case 70 4.3.5. Reduced-order H∞ synthesis: three DOF case 71 4.3.6. Conclusions 76 4.4. Static output feedback design 77 4.5. Industrial examples 82 4.5.1. Mold level control in continuous casting 83 4.5.2. Linear parameter varying control of a missile 83 4.5.3. Internal combustion engine air path control 86 4.5.4. Inertial line-of-sight stabilization 86 4.6. Conclusions 87 CHAPTER 5. PREDICTIVE CONTROL OF HYBRID SYSTEMS 89 5.1. Problematic 89 5.2. Predictive control of power systems 92 5.2.1. Open-loop control and unit commitment 92 5.2.2. Closed-loop control 94 5.3. Optimization procedure 96 5.3.1. Classical optimization methods for unit commitment 96 5.3.2. General synopsis of the optimization procedure 97 5.3.3. Ant colony optimization for the unit commitment 98 5.3.4. Computation of real variables 100 5.3.5. Feasibility criterion 101 5.3.6. Knowledge-based genetic algorithm 102 5.4. Simulation results 107 5.4.1. Real-time updating of produced powers 107 5.4.2. Case study 107 5.5. Conclusions and discussions 108 CONCLUSION 111 BIBLIOGRAPHY 115 INDEX 127

Read more less

Book SynopsisAutomation of linear systems is a fundamental and essential theory. This book deals with the theory of continuous-state automated systems.Table of ContentsPreface. Part 1: System Analysis. Chapter 1. Transfer functions and spectral models (Dominique Beauvois and Yves Tanguy). Chapter 2. State space epresentation (Patrick Boucher and Patrick Turelle). Chapter 3. Discrete-time systems (Philippe Chevrel). Chapter 4. Structural properties of linear systems (Michel Malabre). Chapter 5. Signals: deterministic and statistical models (Eric Le Carpentier). Chapter 6. Kalman's formalism for state stabilization and estimation (Gilles Duc). Chapter 7. Process modeling (Alain Barraud, Suzanne Lesecq and Sylviane Gentil). Chapter 8. Simulation and implementation of continuous time loops (Alain Barraud and Sylviane Gentil). Part 2: System Control. Chapter 9. Analysis by classic scalar approach (Houria Siguerdidjane and Martial Demerlé). Chapter 10. Synthesis of closed loop control systems (Houria Siguerdidjane and Martial Demerlé). Chapter 11. Robust single-variable control through pole placement (Gérard Thomas). Chapter 12. Predictive control (Patrick Boucher and Didier Dumur). Chapter 13. Methodology of the state approach control (Philippe Chevrel). Chapter 14. Multi-variable modal control (Yann Le Gorrec and Jean-François Magni). Chapter 15. Robust H_/LMI framework (Gilles Duc). Chapter 16. Linear time-variant systems (Michel Guglielmi). List of Authors. Index.

Read more less

Book SynopsisThis book gathers together a selection of papers presented at the Joint CTS-HYCON Workshop on Nonlinear and Hybrid Control held at the Paris Sorbonne, France, 10-12 July 2006. The main objective of the Workshop was to promote the exchange of ideas and experiences and reinforce scientific contacts in the large multidisciplinary area of the control of nonlinear and hybrid systems.Table of ContentsPreface. Chapter 1. Hinf Control of Stochastic Hybrid Systems Ellipsoidal Output-Feedback Sets for Hinf Control of a Class of Stochastic Hybrid Systems with State-Dependent Noise. Chapter 2. A Contribution to the Study of Periodic Systems in the Behavioral Approach. Chapter 3. Iteratively Improving Moving Horizon Observers for Repetitive Processes. Chapter 4. Exponential Stability of Dynamic Equations on Time Scales. Chapter 5. Jurdjevic-Quinn Conditions and Discontinuous Bounded Damping Control. Chapter 6. Smooth Approximations of Single-Input Optimal Orbital Transfer using Continuation and Averaging Techniques. Chapter 7. Achieving Stability in Non-holonomic Systems by Means of Switched Control Laws. Chapter 8. Stability of Equilibria for Hybrid Models of Genetic Regulatory Networks. Chapter 9. Tools for Semiglobal Practical Stability Analysis of Cascaded Systems and Applications. Chapter 10. A Rigorous Numerical Algorithm for Controllability. Chapter 11. Dead-locks and Break of Symmetry in Robot Coordination. Chapter 12. Iterative Nonlinear Model Predictive Control: A Review. Chapter 13. Transient Stabilization and Voltage Regulation of a Synchronous Generator. Chapter 14. A Current-based Approach to Wave Reflection Suppression in AC Drives Fed through Long Cables. Chapter 15. Stabilizability of Affine Switching Systems: A Kalman-like Approach. Chapter 16. Observability of Hybrid Automata by Abstraction. Chapter 17. New Convenient Formula for Impedance Change Calculation in Nondestructive Testing Problems by Control of Eddy Currents. Chapter 18. Dynamic Optimization of Nonlinear Bioreactors. Chapter 19. About Stability Analysis for Discrete Time Systems with Time Varying Delays. Chapter 20. Real-time Implementation of Rotor Flux and Speed Control of Induction Motors using Online Rotor Resistance and Load Torque Adaptation. Chapter 21. The On-line Diagnosis of Time Petri Nets Based on Partial Orders. Chapter 22. Optimization Methods for the Sphere Packing Problem on Grassmannians. Chapter 23. Analytical Solution of the Problem on a Magnetohydrodynamic Flow in the Initial Part of a Plane Channel in a Transverse Magnetic Field in Oseen Approximation. Chapter 24. A Formation Control Algorithm using Voronoi Regions. Chapter 25. Output Delay Systems Tracking Using System Centre Approach and Sliding Mode Control. Chapter 26. State-Linearization of Positive Nonlinear Systems; Applications to Lotka-Volterra Controlled Dynamics. Chapter 27. Energy Transfer via Point Interaction Controls. Chapter 28. Further Remarks on Stability Crossing Curves of Distributed Delay Systems. Chapter 29. A New Adaptive Controller for Systems with Multilinear Parameterization. Chapter 30. Hybrid Model Predictive Control Applied on Sewer Networks: The Barcelona Case Study. Chapter 31. Realization Theory of Nonlinear Hybrid Systems. Chapter 32. Adaptive Sliding Mode Observer Based Uncertain Chaotic Masking Communication. Chapter 33. Navier-Stokes Equation on a Plane Bounded Domain: Continuity Properties for Controllability. Chapter 34. Hybrid Predictive Control of a Simulated Chemical Plant. Chapter 35. Robust Identification in Nonlinear Dynamic Process Models. Chapter 36. Generic Families and Generic Bifurcations of Control-Affine Systems. Chapter 37. Sliding Control and Optimization in a Full Bridge Boost Converter. Chapter 38. Feedback Stabilization of the Periodic Operation of an Hybrid Chemical Plant. Chapter 39. Fast Tracking of Poiseuille Trajectories in Navier Stokes 2D Channel Flow. Chapter 40. Some Remarks on Interconnection and Damping Assignment Passivity-Based Control of Mechanical Systems.

Read more less