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Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis
Wei, Qinglai1; Liu, Derong2; Lin, Qiao1
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2017-11-01
Volume28Issue:11Pages:2490-2502
SubtypeArticle
AbstractIn this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Local Iteration Neural Networks Neurodynamic Programming Nonlinear Systems Optimal Control
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TNNLS.2016.2593743
WOS KeywordOPTIMAL TRACKING CONTROL ; ZERO-SUM GAME ; NONLINEAR-SYSTEMS ; FEEDBACK-CONTROL ; CONTROL SCHEME ; LEARNING CONTROL ; REINFORCEMENT ; ALGORITHM ; CONVERGENCE ; NETWORKS
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61233001 ; 61273140 ; 61374105 ; 61533017 ; U1501251)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000413403900003
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13631
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 Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
Recommended Citation
GB/T 7714
Wei, Qinglai,Liu, Derong,Lin, Qiao. Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2017,28(11):2490-2502.
APA Wei, Qinglai,Liu, Derong,&Lin, Qiao.(2017).Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,28(11),2490-2502.
MLA Wei, Qinglai,et al."Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 28.11(2017):2490-2502.
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