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<p>This research addresses the challenge of achieving consensus among a group of unknown agents with nonlinear dynamics, subject to stochastic noises and external influences. To enhance efficiency and reduce communication overhead, an event-based control mechanism is employed, which limits the frequency of controller updates. To handle the unknown nonlinearities, the function approximation technique (FAT), as an universal approximator, is utilized to approximate the agent dynamics. Furthermore, the design complexity is mitigated through a command filtering unit. The proposed distributed control strategy ensures that all signals in the system remain bounded, while simultaneously realizing the system performance. The effectiveness of the introduced approach is validated via comparative simulation scenarios.</p>

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Event-based command-filtered consensus control for uncertain nondeterministic multi-agent systems: a FAT-based learning control scheme

  • 期刊论文

  • 发表日期：

    2025年7月14日

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  • Amir Feizizadeh,
  • Alireza Alfi,
  • Javad Keighobadi,
  • Jinde Cao

摘要

This research addresses the challenge of achieving consensus among a group of unknown agents with nonlinear dynamics, subject to stochastic noises and external influences. To enhance efficiency and reduce communication overhead, an event-based control mechanism is employed, which limits the frequency of controller updates. To handle the unknown nonlinearities, the function approximation technique (FAT), as an universal approximator, is utilized to approximate the agent dynamics. Furthermore, the design complexity is mitigated through a command filtering unit. The proposed distributed control strategy ensures that all signals in the system remain bounded, while simultaneously realizing the system performance. The effectiveness of the introduced approach is validated via comparative simulation scenarios.