CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 平行控制
Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems
Wei Qing-Lai1; Song Rui-Zhuo2; Sun Qiu-Ye3; Xiao Wen-Dong2
Source PublicationCHINESE PHYSICS B
2015-09-01
Volume24Issue:9
SubtypeArticle
AbstractThis paper estimates an off-policy integral reinforcement learning (IRL) algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton-Jacobi-Bellman (HJB) equation, an off-policy IRL algorithm is proposed. It is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method.
KeywordAdaptive Dynamic Programming Approximate Dynamic Programming Chaotic System Optimal Tracking Control
WOS HeadingsScience & Technology ; Physical Sciences
DOI10.1088/1674-1056/24/9/090504
WOS KeywordATTRACTOR ; DYNAMICS ; DESIGN
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61304079 ; Beijing Natural Science Foundation, China(4132078 ; China Postdoctoral Science Foundation(2013M530527) ; Fundamental Research Funds for the Central Universities, China(FRF-TP-14-119A2) ; Open Research Project from State Key Laboratory of Management and Control for Complex Systems, China(20150104) ; 61374105) ; 4143065)
WOS Research AreaPhysics
WOS SubjectPhysics, Multidisciplinary
WOS IDWOS:000363325200021
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10493
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 Sci & Technol, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
3.Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China
Recommended Citation
GB/T 7714
Wei Qing-Lai,Song Rui-Zhuo,Sun Qiu-Ye,et al. Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems[J]. CHINESE PHYSICS B,2015,24(9).
APA Wei Qing-Lai,Song Rui-Zhuo,Sun Qiu-Ye,&Xiao Wen-Dong.(2015).Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems.CHINESE PHYSICS B,24(9).
MLA Wei Qing-Lai,et al."Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems".CHINESE PHYSICS B 24.9(2015).
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