基于相对输出信息的多智能体系统分布式故障检测
作者:
作者单位:

同济大学

作者简介:

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中图分类号:

TP277

基金项目:

科技创新2030—


Distributed fault detection of multi-agent system based on relative output information
Author:
Affiliation:

Tongji University

Fund Project:

National Key R&D Program of China (2020AAA0108100); National Natural Science Foundation of China (62103304); Shanghai Sailing Program (21YF1450500); Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100); Shanghai Municipal Commission of Science and Technology Project (19511132101)

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    摘要:

    本文针对一类邻居控制信息未知,且节点只能获得相对输出信息的多智能体系统,研究了基于未知输入观测器的分布式故障检测问题,实现了节点对自身及邻居故障的实时检测.首先,通过对节点动力学模型进行分解与变换构造出基于相对输出信息的故障检测参考模型,并给出了未知输入观测器的存在性证明;接着,设计了不依赖邻居节点控制信息的未知输入观测器,突破了控制信息缺失导致观测器失效的理论难题;最后,借助未知输入观测器设计故障检测算法,并完成了算法的分布式实现.仿真结果验证了本文所述方法的有效性与先进性.

    Abstract:

    For a class of multi-agent systems where the control information of neighbor nodes is unknown and only local relative output information is available for each agent, the distributed fault detection problem based on the unknown input observers is investigated in this paper, and the real-time fault detection of agent itself and its neighbors is realized. First, by decomposing and transforming the node dynamics, a reference model for fault detection based on the relative output information is constructed, and the existence of the unknown input observer is proved; then, the unknown input observer that decoupled from the control information of neighbor nodes is designed, which breaks the limitation that the lack of control information may lead to the failure of the observer; finally, the fault detection algorithm based on unknown input observer is designed, and the distributed implementation of the algorithm is achieved. The simulation results validate the effectiveness and improvements of the proposed algorithm.

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历史
  • 收稿日期:2021-11-15
  • 最后修改日期:2022-11-09
  • 录用日期:2022-03-28
  • 在线发布日期: 2022-04-17
  • 出版日期: