Dynamic event-triggered tolerant containment control protocol for discrete multiagent systems based on finite index policy iteration algorithm
For tolerant containment control of multi-agent systems, considering the challenges in modeling and the impact of actuator faults on system security and reliability, a finite index dynamic event-triggered policy iteration algorithm is proposed. This algorithm only requires input and output data, wit...
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| Vydáno v: | ISA transactions Ročník 158; s. 21 - 31 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Elsevier Ltd
01.03.2025
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| ISSN: | 0019-0578, 1879-2022, 1879-2022 |
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| Abstract | For tolerant containment control of multi-agent systems, considering the challenges in modeling and the impact of actuator faults on system security and reliability, a finite index dynamic event-triggered policy iteration algorithm is proposed. This algorithm only requires input and output data, without relying on system models, and simultaneously considers the faults and energy consumption issues to improve the system reliability and save energy consumption. The conditions are provided to demonstrate the convergence and optimality of the algorithm, including a convergence speed, that is, the number of iterations required for convergence is finite. For the convenience of practical implementation, an actor–critic structure is adopted and an actor network weight tuning law with actuator fault factors is designed to more accurately approximate the control protocol in policy iteration algorithm. In addition, an event-triggered mechanism is employed in saving computational resources. Finally, simulation results verify the efficiency of the designed algorithm.
•Simultaneously consider the system’s tolerance and energy consumption issues.•The convergence and optimality proofs for the algorithm are provided.•The actor network weight is adjusted according to the actuator fault factors.•The dynamic event-triggered mechanism saves computing resources. |
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| AbstractList | For tolerant containment control of multi-agent systems, considering the challenges in modeling and the impact of actuator faults on system security and reliability, a finite index dynamic event-triggered policy iteration algorithm is proposed. This algorithm only requires input and output data, without relying on system models, and simultaneously considers the faults and energy consumption issues to improve the system reliability and save energy consumption. The conditions are provided to demonstrate the convergence and optimality of the algorithm, including a convergence speed, that is, the number of iterations required for convergence is finite. For the convenience of practical implementation, an actor–critic structure is adopted and an actor network weight tuning law with actuator fault factors is designed to more accurately approximate the control protocol in policy iteration algorithm. In addition, an event-triggered mechanism is employed in saving computational resources. Finally, simulation results verify the efficiency of the designed algorithm.
•Simultaneously consider the system’s tolerance and energy consumption issues.•The convergence and optimality proofs for the algorithm are provided.•The actor network weight is adjusted according to the actuator fault factors.•The dynamic event-triggered mechanism saves computing resources. For tolerant containment control of multi-agent systems, considering the challenges in modeling and the impact of actuator faults on system security and reliability, a finite index dynamic event-triggered policy iteration algorithm is proposed. This algorithm only requires input and output data, without relying on system models, and simultaneously considers the faults and energy consumption issues to improve the system reliability and save energy consumption. The conditions are provided to demonstrate the convergence and optimality of the algorithm, including a convergence speed, that is, the number of iterations required for convergence is finite. For the convenience of practical implementation, an actor-critic structure is adopted and an actor network weight tuning law with actuator fault factors is designed to more accurately approximate the control protocol in policy iteration algorithm. In addition, an event-triggered mechanism is employed in saving computational resources. Finally, simulation results verify the efficiency of the designed algorithm. For tolerant containment control of multi-agent systems, considering the challenges in modeling and the impact of actuator faults on system security and reliability, a finite index dynamic event-triggered policy iteration algorithm is proposed. This algorithm only requires input and output data, without relying on system models, and simultaneously considers the faults and energy consumption issues to improve the system reliability and save energy consumption. The conditions are provided to demonstrate the convergence and optimality of the algorithm, including a convergence speed, that is, the number of iterations required for convergence is finite. For the convenience of practical implementation, an actor-critic structure is adopted and an actor network weight tuning law with actuator fault factors is designed to more accurately approximate the control protocol in policy iteration algorithm. In addition, an event-triggered mechanism is employed in saving computational resources. Finally, simulation results verify the efficiency of the designed algorithm.For tolerant containment control of multi-agent systems, considering the challenges in modeling and the impact of actuator faults on system security and reliability, a finite index dynamic event-triggered policy iteration algorithm is proposed. This algorithm only requires input and output data, without relying on system models, and simultaneously considers the faults and energy consumption issues to improve the system reliability and save energy consumption. The conditions are provided to demonstrate the convergence and optimality of the algorithm, including a convergence speed, that is, the number of iterations required for convergence is finite. For the convenience of practical implementation, an actor-critic structure is adopted and an actor network weight tuning law with actuator fault factors is designed to more accurately approximate the control protocol in policy iteration algorithm. In addition, an event-triggered mechanism is employed in saving computational resources. Finally, simulation results verify the efficiency of the designed algorithm. |
| Author | Al Mamun, Abdullah Yan, Shuya Qian, Huaming Li, Xiaocong |
| Author_xml | – sequence: 1 givenname: Shuya orcidid: 0000-0002-7923-5595 surname: Yan fullname: Yan, Shuya email: ya199367@hrbeu.edu.cn organization: College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China – sequence: 2 givenname: Xiaocong surname: Li fullname: Li, Xiaocong email: xiaocongli@eitech.edu.cn, xiaocong@nus.edu.sg organization: Eastern Institute of Technology, Ningbo, Zhejiang, 315200, China – sequence: 3 givenname: Huaming surname: Qian fullname: Qian, Huaming email: qianhuaming@hrbeu.edu.cn organization: College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China – sequence: 4 givenname: Abdullah surname: Al Mamun fullname: Al Mamun, Abdullah email: eleaam@nus.edu.sg organization: Department of Electrical and Computer Engineering, National University of Singapore, 117538, Singapore |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39818510$$D View this record in MEDLINE/PubMed |
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| Keywords | Time-varying actuator faults Policy iteration algorithm Tolerant containment control Dynamic event-triggered mechanism Reinforcement learning |
| Language | English |
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