Distributed Fault Detection and Isolation of Large-Scale Discrete-Time Nonlinear Systems: An Adaptive Approximation Approach

• Published in: IEEE transactions on automatic control Vol. 57; no. 2; pp. 275 - 290
• Main Authors: Ferrari, R. M. G., Parisini, T., Polycarpou, M. M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive estimation; Applied sciences; Approximation; Approximation methods; Computer science; control theory; systems; Control theory. Systems; distributed fault detection and isolation; Dynamical systems; Exact sciences and technology; Fault detection; Fault diagnosis; Faults; Indexes; Interconnection; large-scale system; Large-scale systems; Mathematical analysis; Mathematical models; Modelling and identification; Monitoring; Nonlinear dynamics; nonlinear systems; Silicon; Studies; Capability index; Scalability; Non linear control; Detectability; Time scale; Adaptive estimation; Dynamical system; Non linear system; Consensus; large-scale system; distributed fault detection and isolation; nonlinear systems; Uncertain system; Observer; Discrete time; Large scale; System identification; Dynamic model; Fault diagnostic; Large scale system
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2011.2164734

This paper deals with the problem of designing a distributed fault detection and isolation methodology for nonlinear uncertain large-scale discrete-time dynamical systems. As a divide et impera approach is used to overcome the scalability issues of a centralized implementation, the large scale system being monitored is 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. 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 overlapping subsystems. Theoretical results are provided to characterize the detection and isolation capabilities of the proposed distributed scheme. Finally, simulation results are reported showing the effectiveness of the proposed methodology.