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Event-Triggered Optimal Parallel Tracking Control for Discrete-Time Nonlinear Systems

文献类型：期刊论文

作者Lu, Jingwei1,2; Wei, Qinglai1,2; Liu, Yujia1,2; Zhou, Tianmin1,2; Wang, Fei-Yue1,3,4
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2021-04-27
页码13
关键词Nonlinear systems Trajectory Optimal control Control systems Mathematical model Steady-state Dynamic programming Adaptive dynamic programming (ADP) event-triggered neural network (NN) nonlinear optimal control parallel control parallel system tracking control
ISSN号2168-2216
DOI10.1109/TSMC.2021.3073429
通讯作者Wang, Fei-Yue(feiyue.wang@ia.ac.cn)
英文摘要A novel event-triggered optimal tracking control (ETOTC) method is developed for discrete-time nonlinear systems in this study. For the time-invariant desired trajectory, we prove that the tracking error is asymptotically stable, and an upper bound of the real performance index can be predetermined by a design parameter. For the time-varying desired trajectory, the developed triggering condition reduces communication costs by relaxing the restriction of the asymptotic stability of the closed-loop system, and we prove that the tracking error is uniformly ultimately bounded (UUB). The developed ETOTC method entails obtaining the next state of the real system. Therefore, a parallel control approach is proposed to predict the next state by constructing a parallel system for the real system. Neural networks (NNs) and adaptive dynamic programming (ADP) techniques are utilized in the parallel control approach. Moreover, the stability analysis of the closed-loop system is shown, and the tracking error and NN weight estimation errors are proved to be UUB using the Lyapunov approach. Finally, we validate the developed ETOTC method through two simulations.
资助项目National Key Research and Development Program of China[2018AAA0101502] ; Science and Technology Project of State Grid Corporation of China (SGCC) fundamental theory of human-inthe-loop hybrid-augmented intelligence for power grid dispatch and control
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
WOS记录号WOS:000732109800001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of China ; Science and Technology Project of State Grid Corporation of China (SGCC) fundamental theory of human-inthe-loop hybrid-augmented intelligence for power grid dispatch and control
源URL[http://ir.ia.ac.cn/handle/173211/46911]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
中国科学院自动化研究所
通讯作者Wang, Fei-Yue
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 Artificial Intelligence, Beijing 100049, Peoples R China
3.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
4.Macau Univ Sci & Technol, Inst Syst Engn, Macau, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Jingwei,Wei, Qinglai,Liu, Yujia,et al. Event-Triggered Optimal Parallel Tracking Control for Discrete-Time Nonlinear Systems[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021:13.
APA Lu, Jingwei,Wei, Qinglai,Liu, Yujia,Zhou, Tianmin,&Wang, Fei-Yue.(2021).Event-Triggered Optimal Parallel Tracking Control for Discrete-Time Nonlinear Systems.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,13.
MLA Lu, Jingwei,et al."Event-Triggered Optimal Parallel Tracking Control for Discrete-Time Nonlinear Systems".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021):13.

入库方式： OAI收割

来源：自动化研究所

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