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Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems
Wei, Qinglai; Liu, Derong; Yang, Xiong
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2015-04-01
Volume26Issue:4Pages:866-879
SubtypeArticle
AbstractIn 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.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Generalized Policy Iteration Neural Networks (Nns) Neurodynamic Programming Nonlinear Systems Optimal Control Reinforcement Learning
WOS HeadingsScience & Technology ; Technology
WOS KeywordDYNAMIC-PROGRAMMING ALGORITHM ; OPTIMAL TRACKING CONTROL ; ADAPTIVE OPTIMAL-CONTROL ; ZERO-SUM GAMES ; UNKNOWN DYNAMICS ; CONTROL SCHEME ; POLICY ITERATION ; LINEAR-SYSTEMS ; CRITIC DESIGNS ; HJB SOLUTION
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000351835900017
Citation statistics
Cited Times:81[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8122
Collection复杂系统管理与控制国家重点实验室_平行控制
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
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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