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This paper investigates the problem of distributed optimal fault-tolerant control (DOFTC) for learning-based linear multi-agent systems (MASs). By defining the new quadratic performance index (QPI), the DOFTC is designed, and the necessary and sufficient conditions for the optimal control (OC) to minimize the QPI are established. Especially when the dynamic matrix of the system is unknown, using adaptive dynamic programming (ADP) technology, a new iterative algorithm is proposed to calculate the feedback gain of the system, so as to find DOFTC. In addition, a topology can be a directed graph. Finally, the validity is verified by a simulation example.

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ADP-Based Distributed Learning Optimal Control for Linear Multi-agent Systems with Actuator Faults

  • 会议论文

  • 发表日期：

    2025年

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  • Sijin Shi,
  • Meng Cui,
  • Jing Ma,
  • Xin Wang

摘要

This paper investigates the problem of distributed optimal fault-tolerant control (DOFTC) for learning-based linear multi-agent systems (MASs). By defining the new quadratic performance index (QPI), the DOFTC is designed, and the necessary and sufficient conditions for the optimal control (OC) to minimize the QPI are established. Especially when the dynamic matrix of the system is unknown, using adaptive dynamic programming (ADP) technology, a new iterative algorithm is proposed to calculate the feedback gain of the system, so as to find DOFTC. In addition, a topology can be a directed graph. Finally, the validity is verified by a simulation example.