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

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.