A sliding mode observer for monitoring and fault estimation in a network of dynamical systems

SUMMARY In this paper, a novel fault estimation strategy is proposed for a network of dynamical systems at a supervisory monitoring level. The network nodes include linear and Lipschitz nonlinear dynamics and time-varying coupling strength. The aim is to enhance the autonomy level of this class of systems by means of this inherently robust, nonlinear strategy based on sliding mode ideas. The faults are reconstructed from the equivalent output error injection signal which is used to maintain sliding. A key facet of the strategy is that the synthesis of the sliding mode observer for the network depends solely on the dynamics of an individual node of the network. The theoretical results developed in the paper are demonstrated with an example consisting of a network of pendulums. Copyright © 2013 John Wiley & Sons, Ltd.

[1]  A. Levant.  Robust exact differentiation via sliding mode technique , 1998 .

[2]  L. Fridman,et al.  High-order sliding modes observation , 2008, 2008 International Workshop on Variable Structure Systems.

[3]  L. Fridman,et al.  Higher‐order sliding‐mode observer for state estimation and input reconstruction in nonlinear systems , 2008 .

[4]  Christopher Edwards,et al.  Sliding mode control : theory and applications , 1998 .

[5]  Ji Xiang,et al.  On the V-stability of complex dynamical networks , 2007, Autom..

[6]  Mehrdad Saif,et al.  Actuator fault diagnosis for uncertain linear systems using a high‐order sliding‐mode robust differentiator (HOSMRD) , 2008 .

[7]  T. Floquet,et al.  On Sliding Mode Observers for Systems with Unknown Inputs , 2006, International Workshop on Variable Structure Systems, 2006. VSS'06..

[8]  M. F. Hassan,et al.  Fault detection in large-scale stochastic dynamic systems , 1992 .

[9]  Christopher Edwards,et al.  HOSM observer for a class of non-minimum phase causal nonlinear MIMO systems , 2008 .

[10]  Milos S. Stankovic,et al.  Consensus Based Overlapping Decentralized Estimator , 2009, IEEE Transactions on Automatic Control.

[11]  Guanrong Chen,et al.  Pinning control of scale-free dynamical networks , 2002 .

[12]  Christopher Edwards,et al.  Sliding mode observers for robust detection and reconstruction of actuator and sensor faults , 2003 .

[13]  L. Fridman,et al.  Exact state estimation for linear systems with unknown inputs based on hierarchical super‐twisting algorithm , 2007 .

[14]  Alessandro Casavola,et al.  A Generic Strategy for Fault-Tolerance in Control Systems Distributed Over a Network , 2007, Eur. J. Control.

[15]  L. Fridman,et al.  High-Order Sliding-Mode Observation of Linear Systems with Unknown Inputs , 2008 .

[16]  Siro Pillosu,et al.  Decentralised state estimation for linear systems with unknown inputs: a consensus-based approach , 2011 .

[17]  Christopher Edwards,et al.  A comparison of sliding mode and unknown input observers for fault reconstruction , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[18]  Halim Alwi,et al.  Sliding mode estimation schemes for incipient sensor faults , 2009, Autom..

[19]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[20]  Christopher Edwards,et al.  Robust decentralized actuator fault detection and estimation for large-scale systems using a sliding mode observer , 2008, Int. J. Control.

[21]  Sarah K. Spurgeon,et al.  Sliding mode observers for fault detection and isolation , 2000, Autom..

[22]  C. Edwards,et al.  Rank constrained stabilization of complex networks , 2008, 2008 American Control Conference.

[23]  Engin Yaz,et al.  Sliding-Mode Adaptive Observer Approach to Chaotic Synchronization , 2000 .

[24]  Khashayar Khorasani,et al.  Actuator Fault Detection and Isolation for a Network of Unmanned Vehicles , 2009, IEEE Transactions on Automatic Control.

[25]  M. Saif,et al.  Robust Fault Detection and Diagnosis for a Multiple Satellite Formation Flying System Using Second Order Sliding Mode and Wavelet Networks , 2007, 2007 American Control Conference.

[26]  Jeff S. Shamma,et al.  A decomposition approach to distributed control of spatially invariant systems , 2006, IEEE Transactions on Automatic Control.