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Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design | |
Wang, Ding1,2,3![]() | |
发表期刊 | IEEE TRANSACTIONS ON CYBERNETICS
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2017-10-01 | |
卷号 | 47期号:10页码:3417-3428 |
文章类型 | Article |
摘要 | In this paper, we aim at improving the critic learning criterion to cope with the event-based nonlinear H-infinity state feedback control design. First of all, the H-infinity control problem is regarded as a two-player zero-sum game and the adaptive critic mechanism is used to achieve the minimax optimization under event-based environment. Then, based on an improved updating rule, the event-based optimal control law and the time-based worst-case disturbance law are obtained approximately by training a single critic neural network. The initial stabilizing control is no longer required during the implementation process of the new algorithm. Next, the closed-loop system is formulated as an impulsive model and its stability issue is handled by incorporating the improved learning criterion. The infamous Zeno behavior of the present event-based design is also avoided through theoretical analysis on the lower bound of the minimal intersample time. Finally, the applications to an aircraft dynamics and a robot arm plant are carried out to verify the efficient performance of the present novel design method. |
关键词 | H-infinity Control Adaptive Systems Adaptive/approximate Dynamic Programming Critic Network Event-based Design Learning Criterion Neural Control |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TCYB.2017.2653800 |
关键词[WOS] | Continuous-time Systems ; State-feedback Control ; Tracking Control ; Algorithm ; Iteration |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | Beijing Natural Science Foundation(4162065) ; National Natural Science Foundation of China(51529701 ; U.S. National Science Foundation(ECCS 1053717) ; SKLMCCS ; 61304086 ; U1501251 ; 61533017 ; 61233001 ; 61273140 ; 61520106009) |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
WOS记录号 | WOS:000409311800038 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/20717 |
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, Sch Comp & Control Engn, Beijing 100049, Peoples R China 3.Univ Rhode Isl, Dept Elect Comp & Biomed Engn, Kingston, RI 02881 USA 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,He, Haibo,Liu, Derong. Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design[J]. IEEE TRANSACTIONS ON CYBERNETICS,2017,47(10):3417-3428. |
APA | Wang, Ding,He, Haibo,&Liu, Derong.(2017).Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design.IEEE TRANSACTIONS ON CYBERNETICS,47(10),3417-3428. |
MLA | Wang, Ding,et al."Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design".IEEE TRANSACTIONS ON CYBERNETICS 47.10(2017):3417-3428. |
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