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Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control
Zhu, Yuanheng1,2; Zhao, Dongbin1,2; He, Haibo3
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
ISSN2168-2216
2020-11-01
Volume50Issue:11Pages:3959-3971
Corresponding AuthorHe, Haibo(he@ele.uri.edu)
AbstractFor systems that can only be locally stabilized, control laws and their effective regions are both important. In this paper, invariant policy iteration is proposed to solve the optimal control of discrete-time systems. At each iteration, a given policy is evaluated in its invariantly admissible region, and a new policy and a new region are updated for the next iteration. Theoretical analysis shows the method is regionally convergent to the optimal value and the optimal policy. Combined with sum-of-squares polynomials, the method is able to achieve the near-optimal control of a class of discrete-time systems. An invariant adaptive dynamic programming algorithm is developed to extend the method to scenarios where system dynamics is not available. Online data are utilized to learn the near-optimal policy and the invariantly admissible region. Simulated experiments verify the effectiveness of our method.
KeywordOptimal control Discrete-time systems Heuristic algorithms Dynamic programming Convergence Artificial intelligence Nonlinear systems Adaptive dynamic programming discrete-time systems invariant admissibility optimal control policy iteration sum of squares
DOI10.1109/TSMC.2019.2911900
WOS KeywordNONLINEAR-SYSTEMS ; POLICY ITERATION ; STABILITY ; SUM
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61603382]
Funding OrganizationNational Natural Science Foundation of China
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000578826300003
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/42180
Collection中国科学院自动化研究所
Corresponding AuthorHe, Haibo
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Univ Rhode Isl, Dept Elect Comp & Biomed Engn, Kingston, RI 02881 USA
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhu, Yuanheng,Zhao, Dongbin,He, Haibo. Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2020,50(11):3959-3971.
APA Zhu, Yuanheng,Zhao, Dongbin,&He, Haibo.(2020).Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,50(11),3959-3971.
MLA Zhu, Yuanheng,et al."Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 50.11(2020):3959-3971.
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