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Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approach
Wang, Ding1; Liu, Derong1,2; Wei, Qinglai1
Source PublicationNEUROCOMPUTING
2012-02-15
Volume78Issue:1Pages:14-22
SubtypeArticle
AbstractIn this paper, a finite-horizon neuro-optimal tracking control strategy for a class of discrete-time nonlinear systems is proposed. Through system transformation, the optimal tracking problem is converted into designing a finite-horizon optimal regulator for the tracking error dynamics. Then, with convergence analysis in terms of cost function and control law, the iterative adaptive dynamic programming (ADP) algorithm via heuristic dynamic programming (HDP) technique is introduced to obtain the finite-horizon optimal tracking controller which makes the cost function close to its optimal value within an epsilon-error bound. Three neural networks are used as parametric structures to implement the algorithm, which aims at approximating the cost function, the control law, and the error dynamics, respectively. Two simulation examples are included to complement the theoretical discussions. (C) 2011 Elsevier B.V. All rights reserved.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming Approximate Dynamic Programming Finite-horizon Optimal Tracking Control Learning Control Neural Networks Reinforcement Learning
WOS HeadingsScience & Technology ; Technology
WOS KeywordCRITIC DESIGNS ; CONTROL SCHEME ; NETWORKS ; REINFORCEMENT
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000298528200003
Citation statistics
Cited Times:114[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3873
Collection复杂系统管理与控制国家重点实验室_智能化团队
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing 100190, Peoples R China
2.Univ Illinois, Dept Elect & Comp Engn, Chicago, IL 60607 USA
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Ding,Liu, Derong,Wei, Qinglai. Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approach[J]. NEUROCOMPUTING,2012,78(1):14-22.
APA Wang, Ding,Liu, Derong,&Wei, Qinglai.(2012).Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approach.NEUROCOMPUTING,78(1),14-22.
MLA Wang, Ding,et al."Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approach".NEUROCOMPUTING 78.1(2012):14-22.
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