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Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Convergence Analysis
Wei, Qinglai1; Lewis, Frank L.2,3; Liu, Derong4; Song, Ruizhuo4; Lin, Hanquan1
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
2018-06-01
Volume48Issue:6Pages:875-891
SubtypeArticle
AbstractIn this paper, convergence properties are established for the newly developed discrete-time local value iteration adaptive dynamic programming (ADP) algorithm. The present local iterative ADP algorithm permits an arbitrary positive semidefinite function to initialize the algorithm. Employing a state-dependent learning rate function, for the first time, the iterative value function and iterative control law can be updated in a subset of the state space instead of the whole state space, which effectively relaxes the computational burden. A new analysis method for the convergence property is developed to prove that the iterative value functions will converge to the optimum under some mild constraints. Monotonicity of the local value iteration ADP algorithm is presented, which shows that under some special conditions of the initial value function and the learning rate function, the iterative value function can monotonically converge to the optimum. Finally, three simulation examples and comparisons are given to illustrate the performance of the developed algorithm.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Local Iteration Neural Networks Neuro-dynamic Programming Nonlinear Systems Optimal Control
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TSMC.2016.2623766
WOS KeywordOPTIMAL TRACKING CONTROL ; OPTIMAL-CONTROL DESIGN ; NONLINEAR-SYSTEMS ; POLICY ITERATION ; CONTROL SCHEME ; FEEDBACK-CONTROL ; LEARNING CONTROL ; ALGORITHM ; REINFORCEMENT ; GAMES
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61233001 ; Fundamental Research Funds for the Central Universities(FRF-TP-15-056A3) ; Open Research Project from SKLMCCS(20150104) ; 61273140 ; 61374105 ; 61503379 ; 61304079 ; 61673054 ; 61533017 ; U1501251)
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000432401600005
Citation statistics
Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13632
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 Texas Arlington, UTA Res Inst, Arlington, TX 76118 USA
3.Northeastern Univ, Shenyang 110036, Liaoning, Peoples R China
4.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
Recommended Citation
GB/T 7714
Wei, Qinglai,Lewis, Frank L.,Liu, Derong,et al. Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Convergence Analysis[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2018,48(6):875-891.
APA Wei, Qinglai,Lewis, Frank L.,Liu, Derong,Song, Ruizhuo,&Lin, Hanquan.(2018).Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Convergence Analysis.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,48(6),875-891.
MLA Wei, Qinglai,et al."Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Convergence Analysis".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 48.6(2018):875-891.
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