BRB-based distributed fault diagnosis for consensus of heterogeneous multi-agent systems
Ruohan Yang, Zhichao Feng · 2021
This paper studies the belief rule base (BRB) expert system based distributed fault diagnosis problem for a group of heterogeneous multi-agent systems (MASs) subject to unpredictable disturbances. First, a novel distributed consensus protocol is developed based on the feedforward approach and internal reference model under directed topology. It is shown that under the proposed consensus protocol, the MASs without fault could achieve bounded consensus asymptotically. Then, novel distributed fault diagnosis models based on BRB are developed for each agent by using the output information of neighbor agents. It should be noted that BRB can handle the information with uncertainty and ambiguity that can address the unpredictable interference in engineering practice. Thus, the proposed BRB based distributed fault diagnosis models for MASs can diagnose the fault and meanwhile eliminate the influence of the unpredictable interference in engineering practice. Finally, a simulation example is provided to illustrate the effectiveness of the approach proposed in this paper.