Distributed Fault Diagnosis for Input-Output Continuous-Time Nonlinear Systems

Abstract In this paper, new results on distributed fault diagnosis of continuous–time nonlinear systems with partial state measurements are proposed. Following an overlapping decomposition framework, the dynamics of a nonlinear uncertain large-scale dynamical systems is described as the interconnection of several subsystems. Each subsystem is monitored by its own Local Fault Diagnoser, based on a set of local estimators. A consensus-based protocol is used to improve the detectability and the isolability of faults affecting variables shared among different subsystems because of the overlapping decomposition. A sufficient condition assuring the convergence of the estimation errors is derived. Time-varying threshold functions guaranteeing no false-positive alarms and theoretical results containing detectability and isolability conditions are presented.

[1]  Antonio Bicchi,et al.  Decentralized intrusion detection for secure cooperative multi-agent systems , 2007, 2007 46th IEEE Conference on Decision and Control.

[2]  Gianfranco Lamperti,et al.  Diagnosis of Large Active Systems , 1999, Artif. Intell..

[3]  Michèle Basseville,et al.  Fault Detection and Isolation in Nonlinear Dynamic Systems: A Combined Input-Output and Local Approach , 1998, Autom..

[4]  Karl Henrik Johansson,et al.  Cyber security analysis of state estimators in electric power systems , 2010, 49th IEEE Conference on Decision and Control (CDC).

[5]  Panos J. Antsaklis,et al.  Control and Communication Challenges in Networked Real-Time Systems , 2007, Proceedings of the IEEE.

[6]  K. Subbarao,et al.  Fault Isolation Using Extrinsic Curvature For Multi-Input-Multi-Output Systems With Nonlinear Fault Models , 2007, 2007 American Control Conference.

[7]  Marios M. Polycarpou,et al.  Distributed Fault Detection and Isolation of Large-Scale Discrete-Time Nonlinear Systems: An Adaptive Approximation Approach , 2012, IEEE Transactions on Automatic Control.

[8]  Nemanja Ilic,et al.  Consensus based overlapping decentralized fault detection and isolation , 2010, 2010 Conference on Control and Fault-Tolerant Systems (SysTol).

[9]  Amir G. Aghdam,et al.  On the structural controllability of multi-agent systems subject to failure: A graph-theoretic approach , 2010, 49th IEEE Conference on Decision and Control (CDC).

[10]  Xiaodong Zhang.  Decentralized fault detection for a class of large-scale nonlinear uncertain systems , 2010, ACC 2010.

[11]  Camille Alain Rabbath,et al.  Decentralized Detection of a Class of Non-Abrupt Faults With Application to Formations of Unmanned Airships , 2009, IEEE Transactions on Control Systems Technology.

[12]  Marios M. Polycarpou,et al.  Robust fault isolation for a class of non-linear input?output systems , 2001 .

[13]  Marios M. Polycarpou,et al.  A distributed fault detection methodology for a class of large-scale uncertain input-output discrete-time nonlinear systems , 2011, IEEE Conference on Decision and Control and European Control Conference.

[14]  Marios M. Polycarpou.  On-line approximators for nonlinear system identification: A unified approach , 1998 .

[15]  GERNOT METZE,et al.  On the Connection Assignment Problem of Diagnosable Systems , 1967, IEEE Trans. Electron. Comput..

[16]  Herbert G. Tanner,et al.  Complex Networked Control Systems: Introduction to the Special Section , 2007 .

[17]  Stephen P. Boyd,et al.  Distributed average consensus with least-mean-square deviation , 2007, J. Parallel Distributed Comput..

[18]  Imad M. Jaimoukha,et al.  Fault detection and isolation for linear discrete-time systems using input/output measurement analysis , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.