A Novel Robust Fault Detection Approach for Heterogeneous Multi-Agent Systems Using Intermediate Estimator

This paper investigates the challenge of fault detection in heterogeneous multi-agent systems with faults and external disturbances. To address the problems posed by system heterogeneity and external interference, a novel two-step fault detection scheme is proposed to enhance detection performance. First, an improved intermediate estimator, which incorporates both homogeneous and heterogeneous information, is employed to more accurately estimate generalized fault signals under external disturbances. The theoretical validation confirms its effectiveness. Subsequently, the characteristics of the heterogeneous parameters are utilized to process the generalized fault signals, leading to the development of an advanced residual generation method that mitigates the impact of system heterogeneity on fault detection. The simulation results validate the efficacy of the proposed methods and highlight their advancements.