Event-Triggered Near-Optimal Control for Unknown Discrete-Time Nonlinear Systems Using Parallel Control
文献类型：期刊论文
| 作者 | Lu, Jingwei2,3 ; Wei, Qinglai2,3; Zhou, Tianmin2,3; Wang, Ziyang1; Wang, Fei-Yue2,3
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| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
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| 出版日期 | 2022-05-06 |
| 页码 | 15 |
| 关键词 | Nonlinear systems Optimal control Control systems Performance analysis Stability criteria Iterative algorithms Heuristic algorithms Adaptive dynamic programming (ADP) event-triggered control near-optimal control parallel control reinforcement learning (RL) unknown nonlinear systems |
| ISSN号 | 2168-2267 |
| DOI | 10.1109/TCYB.2022.3164977 |
| 通讯作者 | Wang, Fei-Yue(feiyue.wang@ia.ac.cn) |
| 英文摘要 | This article uses parallel control to investigate the problem of event-triggered near-optimal control (ETNOC) for unknown discrete-time (DT) nonlinear systems. First, to achieve parallel control, an augmented nonlinear system (ANS) with an augmented performance index (API) is proposed to introduce the control input into the feedback system. The control stability relationship between the ANS and the original system is analyzed, and it is shown that, by choosing a proper API, optimal control of the ANS with the API can be seen as near-optimal control of the original system with the original performance index (OPI). Second, based on parallel control, a novel event-triggered scheme is proposed, and then a novel ETNOC method is developed using the time-triggered optimal value function of the ANS with the API. The control stability is proved, and an upper bound, which is related to the design parameter, is provided for the actual performance index in advance. Then, to implement the developed ETNOC method for unknown DT nonlinear systems, a novel online learning algorithm is developed without reconstructing unknown systems, and neural network (NN) and adaptive dynamic programming (ADP) techniques are employed in the developed algorithm. The convergence of the signals in the closed-loop system (CLS) is shown using the Lyapunov approach, and the assumption of boundedness of input dynamics is not required. Finally, two simulations justify the theoretical conjectures. |
| 资助项目 | National Key Research and Development Program of China[2018AAA0101502] ; National Natural Science Foundation of China[U1811463] ; National Natural Science Foundation of China[62073321] ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRIIACV) |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000795212400001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRIIACV) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/49383]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 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 |
| 通讯作者 | Wang, Fei-Yue |
| 作者单位 | 1.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Jingwei,Wei, Qinglai,Zhou, Tianmin,et al. Event-Triggered Near-Optimal Control for Unknown Discrete-Time Nonlinear Systems Using Parallel Control[J]. IEEE TRANSACTIONS ON CYBERNETICS,2022:15. |
| APA | Lu, Jingwei,Wei, Qinglai,Zhou, Tianmin,Wang, Ziyang,&Wang, Fei-Yue.(2022).Event-Triggered Near-Optimal Control for Unknown Discrete-Time Nonlinear Systems Using Parallel Control.IEEE TRANSACTIONS ON CYBERNETICS,15. |
| MLA | Lu, Jingwei,et al."Event-Triggered Near-Optimal Control for Unknown Discrete-Time Nonlinear Systems Using Parallel Control".IEEE TRANSACTIONS ON CYBERNETICS (2022):15. |
入库方式： OAI收割
来源：自动化研究所
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