Fault detection for discrete-time networked nonlinear systems with incomplete measurements

This article addresses the problem of fault detection (FD) for discrete-time networked systems with global Lipschitz nonlinearities and incomplete measurements, including time delays, packet dropouts and signal quantisation. By utilising a discrete-time homogeneous Markov chain, an improved model which considers packet dropout compensation has been proposed to describe the above network-induced phenomena. We aim to design a mode-dependent fault detection filter (FDF) such that the FD system is asymptotically mean-square stable and satisfies a prescribed attenuation level. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem of Markov jump system with time-varying delay. A sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterised. A numerical example is exploited to show the effectiveness of the results obtained.