Non-Fragile Distributed Fault Estimation for a Class of Nonlinear Time-Varying Systems Over Sensor Networks: The Finite-Horizon Case

This paper is concerned with a new non-fragile distributed fault estimation problem for a class of time-varying systems through sensor networks over a finite horizon. Both randomly occurring nonlinearities and randomly occurring gain variations, whose occurrences are governed by random variables obeying certain probabilistic distributions on the interval <inline-formula><tex-math notation="LaTeX">$[0,1]$</tex-math></inline-formula> are taken into simultaneous consideration. The fault estimation is based on the information not only from the individual sensor, but also from its neighboring ones according to the given topology of the sensor network. The aim of this paper is to design a non-fragile distributed fault estimator such that, in the presence of certain drifts/variations/perturbations of the gain parameters during the implementation, a prescribed average <inline-formula><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance constraint on the estimation error dynamics is satisfied. Based on stochastic analysis techniques, the gain parameters are calculated by solving a series of recursive linear matrix inequalities over a finite horizon. Moreover, a simulation example is provided to show the effectiveness of the proposed fault estimation scheme.