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Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems
Wei, Qinglai1; Liu, Derong2; Lin, Hanquan1; Derong Liu
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
2016-03-01
Volume46Issue:3Pages:840-853
SubtypeArticle
AbstractIn this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Neural Networks Neuro-dynamic Programming Optimal Control Reinforcement Learning Value Iteration
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TCYB.2015.2492242
WOS KeywordOPTIMAL TRACKING CONTROL ; INPUT-OUTPUT DATA ; FEEDBACK-CONTROL ; CONTROL SCHEME ; LEARNING CONTROL ; HJB SOLUTION ; REINFORCEMENT ; APPROXIMATION ; ALGORITHM ; NETWORKS
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61533017 ; 61273140 ; 61374105 ; 61233001)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000370963500022
Citation statistics
Cited Times:86[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11355
Collection复杂系统管理与控制国家重点实验室_平行控制
Corresponding AuthorDerong Liu
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
Recommended Citation
GB/T 7714
Wei, Qinglai,Liu, Derong,Lin, Hanquan,et al. Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems[J]. IEEE TRANSACTIONS ON CYBERNETICS,2016,46(3):840-853.
APA Wei, Qinglai,Liu, Derong,Lin, Hanquan,&Derong Liu.(2016).Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.IEEE TRANSACTIONS ON CYBERNETICS,46(3),840-853.
MLA Wei, Qinglai,et al."Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems".IEEE TRANSACTIONS ON CYBERNETICS 46.3(2016):840-853.
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