Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming

doi:10.1109/TNNLS.2016.2614002

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 深度强化学习

	Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming
	Zhang, Qichao1 ; Zhao, Dongbin1,2 ; Wang, Ding1,3
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2018
卷号	29 期号:1 页码:37-50
文章类型	Article
摘要	In 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.
关键词	Adaptive Dynamic Programming (Adp) Event-based Control Neural Network (Nn) Robust Control Unmatched Uncertainties
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TNNLS.2016.2614002
关键词[WOS]	TRIGGERED CONTROL ; CONTROL DESIGN ; NETWORKS ; SYNCHRONIZATION ; ALGORITHM ; CONSENSUS ; STRATEGY
收录类别	SCI
语种	英语
项目资助者	National 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研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000419558900004
引用统计	被引频次：144[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/173211/14334
专题	多模态人工智能系统全国重点实验室_深度强化学习
通讯作者	Zhao, Dongbin
作者单位	1.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
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 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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