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<p>This paper focuses on the event-triggered optimal control issue for a class of nonlinear strict-feedback multiagent system, which embraces optimization as a fundamental design principle for high-order system control. The reinforcement learning (RL) strategy based on the identifier-actor-critic structure, in the process of optimized backstepping design, is adopted to optimize control performance. Besides that, a novel event-triggered mechanism, which utilizes both on the latest sampled state and a non-negative threshold, is implemented to enhance the efficiency of resource utilization. The computing cost is reduced, and the communication resources are saved by reducing the number of sampling times and the amount of data transmission, thus improving the system efficiency. It is proved that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB) in probability and the Zeno behavior is prevented through the analysis of Lyapunov stability theory. The conduction of two simulation examples is as the final step to substantiate the efficacy of the designed method.</p>

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Event-Triggered Optimized Control for Nonlinear Multiagent Systems via Reinforcement Learning Strategy

  • 期刊论文

  • 发表日期：

    2025年9月12日

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  • Luyu Meng,
  • Xin Wang,
  • Ziming Wang

摘要

This paper focuses on the event-triggered optimal control issue for a class of nonlinear strict-feedback multiagent system, which embraces optimization as a fundamental design principle for high-order system control. The reinforcement learning (RL) strategy based on the identifier-actor-critic structure, in the process of optimized backstepping design, is adopted to optimize control performance. Besides that, a novel event-triggered mechanism, which utilizes both on the latest sampled state and a non-negative threshold, is implemented to enhance the efficiency of resource utilization. The computing cost is reduced, and the communication resources are saved by reducing the number of sampling times and the amount of data transmission, thus improving the system efficiency. It is proved that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB) in probability and the Zeno behavior is prevented through the analysis of Lyapunov stability theory. The conduction of two simulation examples is as the final step to substantiate the efficacy of the designed method.