Distributed Fault Detection and Isolation of Continuous-Time Non-Linear Systems

This paper presents a continuous-time distributed fault detection and isolation methodology for nonlinear uncertain possibly large-scale dynamical systems. The monitored system is modeled as the interconnection of several subsystems and a divide et impera approach using an overlapping decomposition is adopted. Each subsystem is monitored by a Local Fault Diagnoser using the information based on the measured local state of the subsystem as well as the measurements about neighboring states thanks to the subsystem interconnections. The local diagnostic decision is made on the basis of the knowledge of the local subsystem dynamic model and of an adaptive approximation of the interconnection with neighboring subsystems. In order to improve the detectability and isolability of faults affecting variables shared among different subsystems, a consensus-based estimator is designed. Theoretical results are provided to characterize the detection and isolation capabilities of the proposed distributed scheme.