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Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming
Huang, Yuzhu1; Wang, Ding2; Liu, Derong3
Source PublicationNEUROCOMPUTING
2017-11-29
Volume266Pages:128-140
SubtypeArticle
AbstractThis paper is an effort towards developing an optimal learning algorithm to design the bounded robust controller for uncertain nonlinear systems with control constraints using single-network adaptive dynamic programming (ADP). First, the bounded robust control problem is transformed into an optimal control problem of the nominal system by a modified cost function with nonquadratic utility, which is used not only to account for all possible uncertainties, but also to deal with the control constraints. Then based on single-network ADP, an optimal learning algorithm is proposed for the nominal system by a single critic network to approximate the solution of Hamilton-Jacobi-Bellman (HJB) equation. An additional adjusting term is employed to stabilize the system and relax the requirement for an initial stabilizing control. Besides, uniform ultimate boundedness of the closed-loop system is guaranteed by Lyapunov's direct method during the learning process. Moreover, the equivalence of the approximate optimal solution of optimal control problem and the solution of bounded robust control problem is also shown. Finally, four simulation examples are provided to demonstrate the effectiveness of the proposed approach. (C) 2017 Elsevier B.V. All rights reserved.
KeywordNeural Networks Optimal Control Adaptive Dynamic Programming Bounded Robust Control Uncertain Nonlinear Systems
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.neucom.2017.05.030
WOS KeywordCONSTRAINED-INPUT SYSTEMS ; GUARANTEED COST CONTROL ; TIME-SYSTEMS ; HJB SOLUTION ; STABILIZATION
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61233001 ; Beijing Natural Science Foundation(4162065) ; Early Career Development Award of SKLMCCS ; 61533017 ; U1501251)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000408183900013
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20720
Collection复杂系统管理与控制国家重点实验室_平行控制
Affiliation1.Natl Res Ctr Gas Turbine & IGCC Technol, Syst Control Res Sect, Beijing 100084, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
Recommended Citation
GB/T 7714
Huang, Yuzhu,Wang, Ding,Liu, Derong. Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming[J]. NEUROCOMPUTING,2017,266:128-140.
APA Huang, Yuzhu,Wang, Ding,&Liu, Derong.(2017).Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming.NEUROCOMPUTING,266,128-140.
MLA Huang, Yuzhu,et al."Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming".NEUROCOMPUTING 266(2017):128-140.
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