Optimization Books
Springer Nonlinear Optimization and Applications Proceedings of the International School of Mathematics G Stampacchia 21st Workshop Held in Erice Italy 1995 Interdisciplinary Contributions to
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Springer An Introduction to Nonlinear Analysis Theory
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Springer An Introduction to Nonlinear Analysis Applications
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£250.92
Springer Impulsive Control in Continuous and DiscreteContinuous Systems
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£85.85
Springer Handbook of Optimization in Medicine 26 Springer Optimization and Its Applications
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£129.99
Springer Interior Point Methods for Linear Optimization
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Springer Handbook of Optimization in Telecommunications
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Springer Models and Algorithms for Global Optimization Essays Dedicated to Antanas Zilinskas on the Occasion of His 60th Birthday Springer Optimization and on the Occasion of His 60th Birthday 4
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Springer New Approaches to Circle Packing in a Square With Program Codes Springer Optimization and Its Applications 6
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Springer Optimization and Control of Bilinear Systems Theory Algorithms and Applications Springer Optimization and Its Applications 11
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Springer Stochastic Global Optimization 9 Springer Optimization and Its Applications
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Springer Introduction to Applied Optimization
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Springer Fuzzy MultiCriteria Decision Making Springer Optimization and Its Applications Theory and Applications with Recent Developments 16
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Springer Pareto Optimality Game Theory and Equilibria
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Springer Nonlinear Optimization with Engineering Applications
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£64.99
Springer Variational Inequalities with Applications
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Springer Mathematical Optimization and Economic Analysis
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£104.49
Springer Functions of Several Variables
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£43.19
Springer Introduction to Optimal Control Theory
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£59.99
Springer New York Nonlinear Functional Analysis and its Applications III Variational Methods and Optimization 003
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Springer Variational Calculus and Optimal Control
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Springer New York Nonlinear Dynamical Control Systems
Book SynopsisThis volume deals with controllability and observability properties of nonlinear systems, as well as various ways to obtain input-output representations. The emphasis is on fundamental notions as (controlled) invariant distributions and submanifolds, together with algorithms to compute the required feedbacks. Table of Contents1 Introduction.- 2 Manifolds, Vectorfields, Lie Brackets, Distributions.- 3 Controllability and Observability, Local Decompositions.- 4 Input-Output Representations.- 5 State Space Transformation and Feedback.- 6 Feedback Linearization of Nonlinear Systems.- 7 Controlled Invariant Distribution and the Disturbance Decoupling Problem.- 8 The Input-Output Decoupling Problem.- 9 The Input-Output Decoupling Problem.- 10 Local Stability and Stabilization of Nonlinear Systems.- 11 Controlled Invariant Submanifolds and Nonlinear Zero Dynamics.- 12 Mechanical Nonlinear Control Systems.- 13 Controlled Invariance and Decoupling for General Nonlinear Systems.- 14 Discrete-Time Nonlinear Control Systems.
£104.49
Springer New York Linear System Theory Springer Texts in Electrical Engineering
Book SynopsisThis book is the result of our teaching over the years an undergraduate course on Linear Optimal Systems to applied mathematicians and a first-year graduate course on Linear Systems to engineers.Table of Contents1 Introduction.- 1.1 Science and Engineering.- 1.2 Physical Systems, Models, and Representations.- 1.3 Robustness.- 2 The System RepresentationR(•) = [A(•),B(•),C(•),D(•)].- 2.1 Fundamental Properties ofR(•).- 2.1.1 Definitions.- 2.1.2 Structure ofR(•).- 2.1.3 State Transition Matrix.- 2.1.4 State Transition Map and Response Map.- 2.1.5 Impulse Response Matrix.- 2.1.6 Adjoint Equations.- 2.1.7 Linear-Quadratic Optimization.- 2.2 Applications.- 2.2.1 Variational Equation.- 2.2.2 Control Correction Example.- 2.2.3 Optimization Example.- 2.2.4 Periodically Varying Differential Equations.- 2d The Discrete-Time System RepresentationRd(•) = [A(•),B(•),C(•),D(•)].- 2d.1 Fundamental Properties ofRd(•).- 2d.2 Application: Periodically Varying Recursion Equations.- 3 The System RepresentationR= [A,B,C,D], Part I.- 3.1 Preliminaries.- 3.2 General Properties ofR= [A,B,C,D].- 3.2.1 Definition.- 3.2.2 State Transition Matrix.- 3.2.3 The State Transition and Response Map of R.- 3.3 Properties of R when A has a Basis of Eigenvectors.- 3d The Discrete-Time System Representation Rd = [A,B,C,D].- 3d.1 Preliminaries.- 3d.2 General Properties of Rd.- 3d.3 Properties of Rd when A has a Basis of Eigenvectors.- 4 The System Representation R = [A,B,C,D], Part II.- 4.1 Preliminaries.- 4.2 Minimal Polynomial.- 4.3 Decomposition Theorem.- 4.4 The Decomposition of a Linear Map.- 4.5 Jordan Form.- 4.6 Function of a Matrix.- 4.7 Spectral Mapping Theorem.- 4.8 The Linear Map X ? AX+XB.- 5 General System Concepts.- 5.1 Dynamical Systems.- 5.2 Time-Invariant Dynamical Systems.- 5.3 Linear Dynamical Systems.- 5.4 Equivalence.- 6 Sampled Data Systems.- 6.1 Relation BetweenL- and z-Transforms.- 6.2 D/A Converter.- 6.3 A/D Converter.- 6.4 Sampled-Data System.- 6.5 Example.- 7 Stability.- 7.1 I/O Stability.- 7.2 State Related Stability Concepts and Applications.- 7.2.1 Stability of x = A(t)x.- 7.2.2 Bounded Trajectories and Regulation.- 7.2.3 Response to T-Periodic Inputs.- 7.2.4 Periodically Varying System with Periodic Input.- 7.2.5 Slightly Nonlinear Systems.- 7d Stability: The Discrete-Time Case.- 7d.1 I/O Stability.- 7d.2 State Related Stability Concepts.- 7d.2.1 Stability of x(k+1) = A(k)x(k).- 7d.2.2 Bounded Trajectories and Regulation.- 7d.2.3 Response to q-Periodic Inputs.- 8 Controllability and Observability.- 8.1 Controllability and Observability of Dynamical Systems.- 8.2 Controllability of the Pair (A(•),B(•)).- 8.2.1 Controllability of the Pair (A(•),B(•)).- 8.2.2 The Cost of Control.- 8.2.3 Stabilization by Linear State Feedback.- 8.3 Observability of the Pair (C(•),A(•)).- 8.4 Duality.- 8.5 Linear Time-Invariant Systems.- 8.5.1 Observability Properties of the Pair (C,A).- 8.5.2 Controllability of the Pair (A,B).- 8.6 Kalman Decomposition Theorem.- 8.7 Hidden Modes, Stabilizability, and Detectability.- 8.8 Balanced Representations.- 8.9 Robustness of Controllability.- 8d Controllability and Observability: The Discrete-Time Case.- 8d.1 Controllability and Observability of Dynamical Systems.- 8d.2 Reachability and Controllability of the Pair (A(•),B(•)).- 8d.2.1 Controllability of the Pair (A(•),B(•)).- 8d.2.2 The Cost of Control.- 8d.3 Observability of the Pair (C(•),A(•)).- 8d.4 Duality.- 8d.5 Linear Time-Invariant Systems.- 8d.5.1 Observability of the Pair (C,A).- 8d.5.2 Reachability and Controllability of the Pair(A,B).- 8d.6 Kalman Decomposition Theorem.- 8d.7 Stabilizability and Detectability.- 9 Realization Theory.- 9.1 Minimal Realizations.- 9.2 Controllable Canonical Form.- 10 Linear State Feedback and Estimation.- 10.1 Linear State Feedback.- 10.2 Linear Output Injection and State Estimation.- 10.3 State Feedback of the Estimated State.- 10.4 Infinite Horizon Linear Quadratic Optimization.- 10d.4 Infinite Horizon Linear Quadratic Optimization. The Discrete-Time Case.- 11 Unity Feedback Systems.- 11.1 The Feedback System ?c.- 11.1.1 State Space Analysis.- 11.1.2 Special Case:R1andR2have no Unstable Hidden Modes.- 11.1.3 The Discrete-Time Case.- 11.2 Nyquist Criterion.- 11.2.1 The Nyquist Criterion.- 11.2.2 Remarks on the Nyquist Criterion.- 11.2.3 Proof of Nyquist Criterion.- 11.2.4 The Discrete-Time Case.- 11.3 Robustness.- 11.3.1 Robustness With Respect to Plant Perturbations.- 11.3.2 Robustness With Respect to Exogenous Disturbances.- 11.3.3 Robust Regulation.- 11.3.4 Bandwidth-Robustness Tradeoff.- 11.3.5 The Discrete-Time Case.- 11.4 Kharitonov’s Theorem.- 11.4.1 Hurwitz Polynomials.- 11.4.2 Kharitonov’s Theorem.- 11.5 Robust Stability Under Structured Perturbations.- 11.5.1 General Robustness Theorem.- 11.5.2 Special Case: Affine Maps and Convexity.- 11.5.3 The Discrete Time Case.- 11.6 Stability Under Arbitrary Additive Plant Perturbations.- 11.7 Transmission Zeros.- 11.7.1 Single-Input Single-Output Case.- 11.7.2 Multi-Input Multi-Output Case: Assumptions and Definitions.- 11.7.3 Characterization of the Zeros.- 11.7.4 Application to Unity Feedback Systems.- Appendix A Linear Maps and Matrix Analysis.- A.1 Preliminary Notions.- A.2 Rings and Fields.- A.3 Linear Spaces.- A4. Linear Maps.- AS. Matrix Representation.- A.5.1 The Concept of Matrix Representation.- A.5.2 Matrix Representation and Change of Basis.- A.5.3 Range and Null Space: Rank and Nullity.- A.5.4 Echelon Forms of a Matrix.- A.6 Notmed Linear Spaces.- A.6.1 Norms.- A.6.2 Convergence.- A.6.3 Equivalent Norms.- A.6.4 The Lebesgue Spaces 1P and LP [Tay.1].- A.6.5 Continuous Linear Transformations.- A.7 The Adjoint of a Linear Map.- A.7.1 Inner Products.- A.7.2 Adjoints of Continuous Linear Maps.- A.7.3 Properties of the Adjoint.- A.7.4 The Finite Rank Operator Fundamental Lemma.- A.7.5 Singular Value Decomposition (SVD).- Appendix B Differential Equations.- BA Existence and Uniqueness of Solutions.- B.1.1 Assumptions.- B.1.2 Fundamental Theorem.- B.1.3 Construction of a Solution by Iteration.- B.1.4 The Bellman-Gronwall Inequality.- B.1.5 Uniqueness.- B.2 Initial Conditions and Parameter Perturbations.- B.3 Geometric Interpretation and Numerical Calculations.- Appendix C Laplace Transforms.- C.1 Definition of the Laplace Transform.- C.2 Properties of Laplace Transforms.- Appendix D the z-Transform.- D.1 Definition of the z-Transform.- D.2 Properties of the z-Transform.- References.- Abbreviations.- Mathematical Symbols.
£123.49
Springer Practical Optimization Methods With Mathematical Applications
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£113.99
Springer New York A Course in Robust Control Theory
Book SynopsisDuring the 90s robust control theory has seen major advances and achieved a new maturity, centered around the notion of convexity.Trade ReviewFrom the reviews"Because progress in LMI robust control theory has been explosive, only books published in the past 3 or 4 years can hope to adequatetely document the phenomenon. The textbook of Dullerud and Paganini rises admirably to the challenge, starting from the basics of linear algebra and system theory and leading the reader through the key 1990s breakthroughs in LMI robust control theory. To keep things simple, the authors relegate the issue of robustness against nonlinear uncertainties to the citations, focusing attention squarely on the linear case. (...)The book would make an excellent text for a two-semester or two-quarter course for first year graduate students beginning with no prior knowledge of state-space methods. Alternatively, for control students who already have a state-space background."IEEE Transactions on Automatics Control, Vol. 46, No. 9, September 2001Table of Contents0 Introduction.- 1 Preliminaries in Finite Dimensional Space.- 2 State Space System Theory.- 3 Linear Analysis.- 4 Model Realizations and Reduction.- 5 Stabilizing Controllers.- 6 H2 Optimal Control.- 7 H? Synthesis.- 8 Uncertain Systems.- 9 Feedback Control of Uncertain Systems.- 10 Further Topics: Analysis.- 11 Further Topics: Synthesis.- A Some Basic Measure Theory.- A.1 Sets of zero measure.- A.2 Terminology.- Notes and references.- B Proofs of Strict Separation.- Notes and references.- Notes and references.- Notation.- References.
£66.49
Springer Controllability of Dynamical Systems 48 Mathematics and its Applications
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£44.99
Springer Theory of Global Random Search 65 Mathematics and its Applications
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£44.99
Springer Discrete Linear Control Systems 67 Mathematics and its Applications
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£85.49
Springer VectorValued Functions and their Applications 3 Mathematics and its Applications
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Springer Rational Expectations in Macroeconomic Models 26 Advanced Studies in Theoretical and Applied Econometrics
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Springer Program Verification Fundamental Issues in Computer Science 14 Studies in Cognitive Systems
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Springer Global Warming and Economic Development A Holistic Approach to International Policy Cooperation and Coordination 2 Advances in Computational Economics
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Springer Fundamentals of Convex Analysis Duality Separation Representation and Resolution 24 Theory and Decision Library B
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Springer Econometrics of Information and Efficiency 25 Theory and Decision Library B
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Springer Topologies on Closed and Closed Convex Sets 268 Mathematics and Its Applications
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Springer Nonstandard Methods of Analysis 291 Mathematics and Its Applications
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Springer Variational Methods and Complementary Formulations in Dynamics 31 Solid Mechanics and Its Applications
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Springer Stability Theorems in Geometry and Analysis 304 Mathematics and Its Applications
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Springer Finite Element Model Updating in Structural Dynamics 38 Solid Mechanics and Its Applications
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Springer Methods of Model Based Process Control
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Springer Recent Developments in WellPosed Variational Problems 331 Mathematics and Its Applications
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Springer Design and Analysis of Simulation Experiments 339 Mathematics and Its Applications
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Springer Global Optimization in Action Continuous and Lipschitz Optimization Algorithms Implementations and Applications 6 Nonconvex Optimization and Its Applications
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Springer Asymptotic Attainability 383 Mathematics and Its Applications
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Springer Operations Research and Discrete Analysis 391 Mathematics and Its Applications
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Springer The Geometry of HigherOrder Lagrange Spaces Applications to Mechanics and Physics 82 Fundamental Theories of Physics
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Springer Dynamic Impulse Systems Theory and Applications Mathematics and Its Applications 394
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Springer Foundations of Mathematical Optimization Convex Analysis without Linearity Mathematics and Its Applications
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