Distributed fault diagnosis of large-scale discrete-time nonlinear systems: New results on the isolation problem

This paper deals with the problem of designing a distributed fault detection and isolation methodology for nonlinear discrete-time dynamical systems that are modelled as the interconnection of several subsystems. The subsystems are allowed to overlap, thus sharing some state components. For each subsystem, a Local Fault Diagnoser is designed, based on the measured local state of the subsystem as well as the transmitted variables of neighboring states that define 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. A Global Fault Diagnoser is introduced to isolate distributed faults that cannot be isolated locally. The use of a specially-designed consensus-based estimator is proposed in order to improve the detectability and isolability of faults affecting variables shared among different subsystems. Simulation results are utilized to illustrate of the effectiveness of the proposed distributed fault diagnosis methodology.