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Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors
Wei, Qinglai; Liu, Derong; Qinglai Wei
Source PublicationNEUROCOMPUTING
2015-02-03
Volume149Issue:xPages:106-115
SubtypeArticle
AbstractIn this paper, a new infinite horizon neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems is developed. The idea is to use iterative adaptive dynamic programming (ADP) algorithm to obtain the iterative tracking control law which makes the iterative performance index function reach the optimum. When the iterative tracking control law and iterative performance index function in each iteration cannot be accurately obtained, the convergence criteria of the iterative ADP algorithm are established according to the properties with finite approximation errors. If the convergence conditions are satisfied, it shows that the iterative performance index functions can converge to a finite neighborhood of the lowest bound of all performance index functions. Properties of the finite approximation errors for the iterative ADP algorithm are also analyzed. Neural networks are used to approximate the performance index function and compute the optimal control policy, respectively, for facilitating the implementation of the iterative ADP algorithm. Convergence properties of the neural network weights are proven. Finally, simulation results are given to illustrate the performance of the developed method. (C) 2014 Elsevier B.V. All rights reserved.
KeywordAdaptive Dynamic Programming Adaptive Critic Designs Approximate Dynamic Programming Value Iteration Approximation Errors Optimal Tracking Control
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.neucom.2013.09.069
WOS KeywordDYNAMIC-PROGRAMMING ALGORITHM ; ONLINE LEARNING CONTROL ; CRITIC DESIGNS ; REINFORCEMENT ; CONVERGENCE ; ITERATION ; PROOF
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000360028800015
Citation statistics
Cited Times:41[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8958
Collection复杂系统管理与控制国家重点实验室_平行控制
Corresponding AuthorQinglai Wei
AffiliationChinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wei, Qinglai,Liu, Derong,Qinglai Wei. Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors[J]. NEUROCOMPUTING,2015,149(x):106-115.
APA Wei, Qinglai,Liu, Derong,&Qinglai Wei.(2015).Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors.NEUROCOMPUTING,149(x),106-115.
MLA Wei, Qinglai,et al."Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors".NEUROCOMPUTING 149.x(2015):106-115.
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