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Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming
Zhang, Qichao1; Zhao, Dongbin1,2; Wang, Ding1,3
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2018
Volume29Issue:1Pages:37-50
SubtypeArticle
AbstractIn this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.
KeywordAdaptive Dynamic Programming (Adp) Event-based Control Neural Network (Nn) Robust Control Unmatched Uncertainties
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TNNLS.2016.2614002
WOS KeywordTRIGGERED CONTROL ; CONTROL DESIGN ; NETWORKS ; SYNCHRONIZATION ; ALGORITHM ; CONSENSUS ; STRATEGY
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61273136 ; National Key Research and Development Plan(2016YFB0101000) ; Beijing Natural Science Foundation(4162065) ; Research Fund of Tianjin Key Laboratory of Process Measurement and Control(TKLPMC-201612) ; 61573353 ; 61533017 ; 61304086 ; 61603382 ; U1501251)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000419558900004
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14334
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Corresponding AuthorZhao, Dongbin
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Tianjin Univ, Sch Elect Engn & Automat, Tianjin Key Lab Proc Measurement & Control, Tianjin 300072, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Qichao,Zhao, Dongbin,Wang, Ding. Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(1):37-50.
APA Zhang, Qichao,Zhao, Dongbin,&Wang, Ding.(2018).Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(1),37-50.
MLA Zhang, Qichao,et al."Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.1(2018):37-50.
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