Adaptive Critic Nonlinear Robust Control: A Survey
Wang, Ding1,2,3; He, Haibo3; Liu, Derong4
2017-10-01
发表期刊IEEE TRANSACTIONS ON CYBERNETICS
卷号47期号:10页码:3429-3451
文章类型Article
摘要

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H-infinity control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

关键词Adaptive Critic Designs Adaptive/approximate Dynamic Programming (Adp) Boundedness Convergence Neural Networks Optimal Control Reinforcement Learning Robust Control Stability
WOS标题词Science & Technology ; Technology
DOI10.1109/TCYB.2017.2712188
关键词[WOS]Guaranteed Cost Control ; Optimal-control Design ; Discrete-time-systems ; Infinity State-feedback ; Approximate Optimal-control ; Constrained-input Systems ; Optimal Tracking Control ; Learning Optimal-control ; Horizon Optimal-control ; Load-frequency Control
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(51529701 ; Beijing Natural Science Foundation(4162065) ; U.S. National Science Foundation(ECCS 1053717 ; SKLMCCS ; U1501251 ; CMMI 1526835) ; 61533017 ; 61233001 ; 61520106009)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号WOS:000409311800039
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20726
专题复杂系统管理与控制国家重点实验室_平行控制
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, Sch Comp & Control Engn, Beijing 100049, Peoples R China
3.Univ Rhode Isl, Dept Elect Comp & Biomed Engn, Kingston, RI 02881 USA
4.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
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Wang, Ding,He, Haibo,Liu, Derong. Adaptive Critic Nonlinear Robust Control: A Survey[J]. IEEE TRANSACTIONS ON CYBERNETICS,2017,47(10):3429-3451.
APA Wang, Ding,He, Haibo,&Liu, Derong.(2017).Adaptive Critic Nonlinear Robust Control: A Survey.IEEE TRANSACTIONS ON CYBERNETICS,47(10),3429-3451.
MLA Wang, Ding,et al."Adaptive Critic Nonlinear Robust Control: A Survey".IEEE TRANSACTIONS ON CYBERNETICS 47.10(2017):3429-3451.
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