On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear H-infinity Control

doi:10.1109/TNNLS.2016.2642128

CASIA OpenIR > 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

	On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear H-infinity Control
	Wang, Ding1,2 ; Mu, Chaoxu 3; Liu, Derong 4; Ma, Hongwen1,2
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2018-04-01
卷号	29 期号:4 页码:993-1005
文章类型	Article
摘要	In this paper, based on the adaptive critic learning technique, the H-infinity control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear H-infinity control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear H-infinity control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.
关键词	Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Data Driven Control Event Driven Control Hamilton-jacobi-isaacs (Hji) Equation Neural Network Identification Nonlinear H-infinity Control Zero-sum Game
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TNNLS.2016.2642128
关键词[WOS]	ZERO-SUM GAMES ; DISCRETE-TIME-SYSTEMS ; STRICT-FEEDBACK FORM ; LEARNING ALGORITHM ; UNKNOWN DYNAMICS ; STATE-FEEDBACK ; STABILIZATION ; ITERATION ; SCHEME
收录类别	SCI
语种	英语
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:000427859600019
引用统计	被引频次：110[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/173211/21976
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.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 & Informat Engn, Tianjin Key Lab Proc Measurement & Control, Tianjin 300072, Peoples R China 4.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wang, Ding,Mu, Chaoxu,Liu, Derong,et al. On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear H-infinity Control[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(4):993-1005.
APA	Wang, Ding,Mu, Chaoxu,Liu, Derong,&Ma, Hongwen.(2018).On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear H-infinity Control.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(4),993-1005.
MLA	Wang, Ding,et al."On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear H-infinity Control".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.4(2018):993-1005.