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Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors
Wei, Qinglai1,2; Li, Benkai1; Song, Ruizhuo3
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2018-04-01
Volume29Issue:4Pages:1226-1238
SubtypeArticle
AbstractIn this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Generalized Policy Iteration (Gpi) Neural Networks Neurodynamic Programming Nonlinear Systems Optimal Control Reinforcement Learning
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TNNLS.2017.2661865
WOS KeywordDYNAMIC-PROGRAMMING ALGORITHM ; ZERO-SUM GAMES ; NONLINEAR-SYSTEMS ; TRACKING CONTROL ; UNKNOWN DYNAMICS ; VALUE-ITERATION ; CONTROL SCHEME ; REINFORCEMENT ; DESIGN
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:000427859600037
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13634
Collection复杂系统管理与控制国家重点实验室_平行控制
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
Recommended Citation
GB/T 7714
Wei, Qinglai,Li, Benkai,Song, Ruizhuo. Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(4):1226-1238.
APA Wei, Qinglai,Li, Benkai,&Song, Ruizhuo.(2018).Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(4),1226-1238.
MLA Wei, Qinglai,et al."Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.4(2018):1226-1238.
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