Neural-network-based adaptive guaranteed cost control of nonlinear dynamical systems with matched uncertainties
Mu, Chaoxu1; Wang, Ding2
发表期刊NEUROCOMPUTING
2017-07-05
卷号245页码:46-54
文章类型Article
摘要In this paper, we investigate the neural-network-based adaptive guaranteed cost control for continuous time affine nonlinear systems with dynamical uncertainties. Through theoretical analysis, the guaranteed cost control problem is transformed into designing an optimal controller of the associated nominal system with a newly defined cost function. The approach of adaptive dynamic programming (ADP) is involved to implement the guaranteed cost control strategy with the neural network approximation. The stability of the closed-loop system with the guaranteed cost control law, the convergence of the critic network weights and the approximate boundary of the guaranteed cost control law are all analyzed. Two simulation examples have been conducted and all simulation results have indicated the good performance of the developed guaranteed cost control strategy. (C) 2017 Elsevier B.V. All rights reserved.
关键词Adaptive Dynamic Programming (Adp) Guaranteed Cost Control Neural Networks Uncertain Dynamics Stability
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2017.03.047
关键词[WOS]DISCRETE-TIME-SYSTEMS ; SWITCHED NEUTRAL SYSTEMS ; VARYING MIXED DELAYS ; UNKNOWN DYNAMICS ; STABILIZATION ; REINFORCEMENT ; REGRESSION ; ALGORITHM ; DESIGN ; MODEL
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(U1501251 ; Beijing Natural Science Foundation(4162065) ; Tianjin Natural Science Foundation(14JCQNJC05400) ; Research Fund of Tianjin Key Laboratory of Process Measurement and Control(TKLPMC-201612) ; Early Career Development Award of SKLMCCS ; 61533017 ; 61304018 ; 61304086 ; 61411130160)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000400217000005
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被引频次:32[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/15260
专题多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队
作者单位1.Tianjin Univ, Tianjin Key Lab Proc Measurement & Control, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China
2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
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Mu, Chaoxu,Wang, Ding. Neural-network-based adaptive guaranteed cost control of nonlinear dynamical systems with matched uncertainties[J]. NEUROCOMPUTING,2017,245:46-54.
APA Mu, Chaoxu,&Wang, Ding.(2017).Neural-network-based adaptive guaranteed cost control of nonlinear dynamical systems with matched uncertainties.NEUROCOMPUTING,245,46-54.
MLA Mu, Chaoxu,et al."Neural-network-based adaptive guaranteed cost control of nonlinear dynamical systems with matched uncertainties".NEUROCOMPUTING 245(2017):46-54.
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