000			05894nam a2200913 i 4500
001			7927594
003			IEEE
005			20220712205947.0
006			m o d
007			cr |n|||||||||
008			170607s2017 mau ob 001 eng d
019			_a982871319 _a983148954 _a983440309 _a983568456 _a983698970 _a983920719 _a983986575 _a984330878 _a984628591 _a985326830
020			_a9781119132677 _qelectronic bk. : oBook
020			_z9781119132646 _qprint
020			_z1119132673 _qelectronic bk. : oBook
020			_z9781119132653 _qelectronic bk.
020			_z1119132657 _qelectronic bk.
020			_z1119132649
024	7		_a10.1002/9781119132677 _2doi
035			_a(CaBNVSL)mat07927594
035			_a(IDAMS)0b00006485d01d4e
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aTJ217
082	0	4	_a629.8/36 _223
100	1		_aJiang, Yu, _eauthor. _929090
245	1	0	_aRobust adaptive dynamic programming / _cYu Jiang, Zhong-Ping Jiang.
264		1	_aHoboken, New Jersey : _bWiley : _bIEEE Press, _c2017.
264		2	_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2017]
300			_a1 PDF (216 pages).
336			_atext _2rdacontent
337			_aelectronic _2isbdmedia
338			_aonline resource _2rdacarrier
490	1		_aIEEE press series on systems science and engineering
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction -- Adaptive Dynamic Programming for Uncertain Linear Systems -- Semi-Global Adaptive Dynamic Programming -- Global Adaptive Dynamic Programming for Nonlinear Polynomial Systems -- Robust Adaptive Dynamic Programming -- Robust Adaptive Dynamic Programming for Large-Scale Systems -- Robust Adaptive Dynamic Programming as A Theory of Sensorimotor Control.
506			_aRestricted to subscribers or individual electronic text purchasers.
520			_aA comprehensive look at state-of-the-art ADP theory and real-world applications This 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 problems. Explores multiple real-world implementations in power systems with illustrative examples backed up by reusable MATLAB code and Simulink block sets. Provides an overview of nonlinear control, machine learning, and dynamic control. Features discussions of novel applications for RADP theory, including an entire chapter on how it can be used as a computational mechanism of human movement control Robust 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.
530			_aAlso available in print.
538			_aMode of access: World Wide Web
588			_aOnline resource; title from PDF title page (John Wiley, viewed April 20, 2017).
650		0	_aAdaptive control systems. _97063
650		0	_aRobust control. _97064
650		7	_aAdaptive control systems. _2fast _97063
650		7	_aRobust control. _2fast _97064
655		4	_aElectronic books. _93294
695			_aAdaptive systems
695			_aAlgorithm design and analysis
695			_aApproximation algorithms
695			_aAsymptotic stability
695			_aClosed loop systems
695			_aConvergence
695			_aDiscrete wavelet transforms
695			_aDynamic programming
695			_aFeedback control
695			_aInterconnected systems
695			_aLarge-scale systems
695			_aLearning (artificial intelligence)
695			_aLinear systems
695			_aLyapunov methods
695			_aMathematical model
695			_aNonlinear dynamical systems
695			_aNonlinear systems
695			_aOptimal control
695			_aOptimization
695			_aRobustness
695			_aStability analysis
695			_aStochastic systems
695			_aSymmetric matrices
695			_aSystem dynamics
695			_aUncertain systems
695			_aUncertainty
700	1		_aJiang, Zhong-Ping, _eauthor. _929091
710	2		_aIEEE Xplore (Online Service), _edistributor. _929092
710	2		_aWiley, _epublisher. _929093
776	0	8	_cOriginal _z9781119132646 _z1119132649 _w(OCoLC)958796702
830		0	_aIEEE press series on systems science and engineering _98461
856	4	2	_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7927594
942			_cEBK
999			_c74506 _d74506