Robust Adaptive Dynamic Programming

Inbunden, Engelska, 2017

AvYu Jiang,Zhong-Ping Jiang,Yu (MathWorks) Jiang,USA) Jiang, Zhong-Ping (New York University

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A comprehensive look at state-of-the-art ADP theory and real-world applicationsThis book fills a gap in the literature by providing a theoretical framework for integrating techniques from adaptive dynamic programming (ADP) and modern nonlinear control to address data-driven optimal control design challenges arising from both parametric and dynamic uncertainties.Traditional model-based approaches leave much to be desired when addressing the challenges posed by the ever-increasing complexity of real-world engineering systems. An alternative which has received much interest in recent years are biologically-inspired approaches, primarily RADP. Despite their growing popularity worldwide, until now books on ADP have focused nearly exclusively on analysis and design, with scant consideration given to how it can be applied to address robustness issues, a new challenge arising from dynamic uncertainties encountered in common engineering problems. Robust Adaptive Dynamic Programming zeros in on the practical concerns of engineers. The authors develop RADP theory from linear systems to partially-linear, large-scale, and completely nonlinear systems. They provide in-depth coverage of state-of-the-art applications in power systems, supplemented with numerous real-world examples implemented in MATLAB. They also explore fascinating reverse engineering topics, such how ADP theory can be applied to the study of the human brain and cognition. In addition, the book: Covers the latest developments in RADP theory and applications for solving a range of systems’ complexity problemsExplores multiple real-world implementations in power systems with illustrative examples backed up by reusable MATLAB code and Simulink block setsProvides an overview of nonlinear control, machine learning, and dynamic controlFeatures discussions of novel applications for RADP theory, including an entire chapter on how it can be used as a computational mechanism of human movement controlRobust Adaptive Dynamic Programming is both a valuable working resource and an intriguing exploration of contemporary ADP theory and applications for practicing engineers and advanced students in systems theory, control engineering, computer science, and applied mathematics.

Produktinformation

Utgivningsdatum2017-06-23
Mått158 x 239 x 20 mm
Vikt567 g
FormatInbunden
SpråkEngelska
SerieIEEE Press Series on Systems Science and Engineering
Antal sidor216
FörlagJohn Wiley & Sons Inc
ISBN9781119132646

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Yu Jiang, PhD, is a Software Developer of Simulink Control Design at MathWorks. In the past five years, he has published nearly 30 papers and one book chapter on the subject of ADP theory and its applications. He was the recipient of the Shimemura Young Author Prize (with Prof. Z.P.Jiang) at the 9th Asian Control Conference in Istanbul, Turkey, 2013. Zhong-Ping Jiang, PhD, is a Professor of Electrical and Computer Engineering at New York University with a doctorate in automatic control and mathematics. He has authored three books and over 400 journal and conference papers on nonlinear systems and control, dynamic networks, and more.

ABOUT THE AUTHORS xiPREFACE AND ACKNOWLEDGMENTS xiiiACRONYMS xviiGLOSSARY xix1 INTRODUCTION 11.1 From RL to RADP 11.2 Summary of Each Chapter 5References 62 ADAPTIVE DYNAMIC PROGRAMMING FOR UNCERTAIN LINEAR SYSTEMS 112.1 Problem Formulation and Preliminaries 112.2 Online Policy Iteration 142.3 Learning Algorithms 162.4 Applications 242.5 Notes 29References 303 SEMI-GLOBAL ADAPTIVE DYNAMIC PROGRAMMING 353.1 Problem Formulation and Preliminaries 353.2 Semi-Global Online Policy Iteration 383.3 Application 433.4 Notes 46References 464 GLOBAL ADAPTIVE DYNAMIC PROGRAMMING FOR NONLINEAR POLYNOMIAL SYSTEMS 494.1 Problem Formulation and Preliminaries 494.2 Relaxed HJB Equation and Suboptimal Control 524.3 SOS-Based Policy Iteration for Polynomial Systems 554.4 Global ADP for Uncertain Polynomial Systems 594.5 Extension for Nonlinear Non-Polynomial Systems 644.6 Applications 704.7 Notes 81References 815 ROBUST ADAPTIVE DYNAMIC PROGRAMMING 855.1 RADP for Partially Linear Composite Systems 865.2 RADP for Nonlinear Systems 975.3 Applications 1035.4 Notes 109References 1106 ROBUST ADAPTIVE DYNAMIC PROGRAMMING FOR LARGE-SCALE SYSTEMS 1136.1 Stability and Optimality for Large-Scale Systems 1136.2 RADP for Large-Scale Systems 1226.3 Extension for Systems with Unmatched Dynamic Uncertainties 1246.4 Application to a Ten-Machine Power System 1286.5 Notes 132References 1337 ROBUST ADAPTIVE DYNAMIC PROGRAMMING AS A THEORY OF SENSORIMOTOR CONTROL 1377.1 ADP for Continuous-Time Stochastic Systems 1387.2 RADP for Continuous-Time Stochastic Systems 1437.3 Numerical Results: ADP-Based Sensorimotor Control 1537.4 Numerical Results: RADP-Based Sensorimotor Control 1657.5 Discussion 1677.6 Notes 172References 173A BASIC CONCEPTS IN NONLINEAR SYSTEMS 177A.1 Lyapunov Stability 177A.2 ISS and the Small-Gain Theorem 178B SEMIDEFINITE PROGRAMMING AND SUM-OF-SQUARES PROGRAMMING 181B.1 SDP and SOSP 181C PROOFS 183C.1 Proof of Theorem 3.1.4 183C.2 Proof of Theorem 3.2.3 186References 188INDEX 191