Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems

doi:10.1109/TSMC.2015.2417510

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 复杂系统智能机理与平行控制团队

	Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems
	Liu, Derong; Wei, Qinglai; Yan, Pengfei
发表期刊	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
	2015-12-01
卷号	45 期号:12 页码:1577-1591
文章类型	Article
摘要	This paper is concerned with a novel generalized policy iteration algorithm for solving optimal control problems for discrete-time nonlinear systems. The idea is to use an iterative adaptive dynamic programming algorithm to obtain iterative control laws which make the iterative value functions converge to the optimum. Initialized by an admissible control law, it is shown that the iterative value functions are monotonically nonincreasing and converge to the optimal solution of Hamilton-Jacobi-Bellman equation, under the assumption that a perfect function approximation is employed. The admissibility property is analyzed, which shows that any of the iterative control laws can stabilize the nonlinear system. Neural networks are utilized to implement the generalized policy iteration algorithm, by approximating the iterative value function and computing the iterative control law, respectively, to achieve approximate optimal control. Finally, numerical examples are presented to verify the effectiveness of the present generalized policy iteration algorithm.
关键词	Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Generalized Policy Iteration Neural Networks Neuro-dynamic Programming Nonlinear Systems Optimal Control Reinforcement Learning
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TSMC.2015.2417510
关键词[WOS]	OPTIMAL TRACKING CONTROL ; ZERO-SUM GAMES ; LEARNING OPTIMAL-CONTROL ; CONTROL SCHEME ; UNKNOWN DYNAMICS ; APPROXIMATION ERRORS ; CRITIC DESIGNS ; HJB SOLUTION ; REINFORCEMENT ; ALGORITHM
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61034002 ; Beijing Natural Science Foundation(4132078) ; Early Career Development Award of the State Key Laboratory of Management and Control for Complex Systems ; 61233001 ; 61273140 ; 61304086 ; 61374105)
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Cybernetics
WOS记录号	WOS:000366891300009
引用统计	被引频次：105[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10646
专题	多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队
作者单位	Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Liu, Derong,Wei, Qinglai,Yan, Pengfei. Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2015,45(12):1577-1591.
APA	Liu, Derong,Wei, Qinglai,&Yan, Pengfei.(2015).Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,45(12),1577-1591.
MLA	Liu, Derong,et al."Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 45.12(2015):1577-1591.

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Generalized Policy I（1540KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览