Event-triggered robust adaptive critic control for nonlinear disturbed systems
A novel dynamic event-triggered control strategy is proposed by utilizing the adaptive critic learning (ACL) technique for nonlinear continuous-time systems subject to disturbances in this paper. To address the transformation of the robust-optimal control problem, a modified cost function containing...
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| Published in | Nonlinear dynamics Vol. 111; no. 21; pp. 19963 - 19977 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.11.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0924-090X 1573-269X |
| DOI | 10.1007/s11071-023-08862-4 |
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| Abstract | A novel dynamic event-triggered control strategy is proposed by utilizing the adaptive critic learning (ACL) technique for nonlinear continuous-time systems subject to disturbances in this paper. To address the transformation of the robust-optimal control problem, a modified cost function containing the disturbance term is introduced. The dynamic event-triggered controller is obtained by incorporating an internal variable into the static triggering strategy. An ACL method is employed to design static and dynamic triggering controllers. Critic neural networks are used to approximate the cost function and the corresponding Hamilton–Jacobi–Bellman equation, leading to the establishment of adaptive critic event-triggered controllers. Stability analysis of the closed-loop system is also provided, and simulation results demonstrate the effectiveness of the developed dynamic triggering strategy with two examples. |
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| AbstractList | A novel dynamic event-triggered control strategy is proposed by utilizing the adaptive critic learning (ACL) technique for nonlinear continuous-time systems subject to disturbances in this paper. To address the transformation of the robust-optimal control problem, a modified cost function containing the disturbance term is introduced. The dynamic event-triggered controller is obtained by incorporating an internal variable into the static triggering strategy. An ACL method is employed to design static and dynamic triggering controllers. Critic neural networks are used to approximate the cost function and the corresponding Hamilton–Jacobi–Bellman equation, leading to the establishment of adaptive critic event-triggered controllers. Stability analysis of the closed-loop system is also provided, and simulation results demonstrate the effectiveness of the developed dynamic triggering strategy with two examples. |
| Author | Liu, Ao Qiao, Junfei Wang, Ding Zhou, Zihang |
| Author_xml | – sequence: 1 givenname: Ding surname: Wang fullname: Wang, Ding email: dingwang@bjut.edu.cn organization: Faculty of Information Technology, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology – sequence: 2 givenname: Zihang surname: Zhou fullname: Zhou, Zihang organization: Faculty of Information Technology, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology – sequence: 3 givenname: Ao surname: Liu fullname: Liu, Ao organization: Faculty of Information Technology, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology – sequence: 4 givenname: Junfei surname: Qiao fullname: Qiao, Junfei organization: Faculty of Information Technology, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology |
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| Keywords | Adaptive critic learning Dynamic event-triggered control strategies Robust-optimal control design Nonlinear disturbed systems Critic neural networks |
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| SubjectTerms | Adaptive control Automotive Engineering Classical Mechanics Closed loop systems Closed loops Continuous time systems Control Control stability Controllers Cost function Dynamical Systems Electronic mail systems Engineering Euclidean space Feedback control Mechanical Engineering Neural networks Nonlinear control Nonlinear systems Optimal control Original Paper Robust control Stability analysis Vibration |
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| Title | Event-triggered robust adaptive critic control for nonlinear disturbed systems |
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