Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems

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

	Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems
	Wei, Qinglai; Liu, Derong; Yang, Xiong
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2015-04-01
卷号	26 期号:4 页码:866-879
文章类型	Article
摘要	In this paper, a novel iterative adaptive dynamic programming (ADP)-based infinite horizon self-learning optimal control algorithm, called generalized policy iteration algorithm, is developed for nonaffine discrete-time (DT) nonlinear systems. Generalized policy iteration algorithm is a general idea of interacting policy and value iteration algorithms of ADP. The developed generalized policy iteration algorithm permits an arbitrary positive semidefinite function to initialize the algorithm, where two iteration indices are used for policy improvement and policy evaluation, respectively. It is the first time that the convergence, admissibility, and optimality properties of the generalized policy iteration algorithm for DT nonlinear systems are analyzed. Neural networks are used to implement the developed algorithm. Finally, numerical examples are presented to illustrate the performance of the developed algorithm.
关键词	Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Generalized Policy Iteration Neural Networks (Nns) Neurodynamic Programming Nonlinear Systems Optimal Control Reinforcement Learning
WOS标题词	Science & Technology ; Technology
关键词[WOS]	DYNAMIC-PROGRAMMING ALGORITHM ; OPTIMAL TRACKING CONTROL ; ADAPTIVE OPTIMAL-CONTROL ; ZERO-SUM GAMES ; UNKNOWN DYNAMICS ; CONTROL SCHEME ; POLICY ITERATION ; LINEAR-SYSTEMS ; CRITIC DESIGNS ; HJB SOLUTION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000351835900017
引用统计	被引频次：127[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/173211/8122
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	Wei, Qinglai,Liu, Derong,Yang, Xiong. Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2015,26(4):866-879.
APA	Wei, Qinglai,Liu, Derong,&Yang, Xiong.(2015).Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,26(4),866-879.
MLA	Wei, Qinglai,et al."Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 26.4(2015):866-879.

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