On ℋ∞ Estimation of Randomly Occurring Faults for A Class of Nonlinear Time-Varying Systems With Fading Channels

This paper is concerned with the finite-horizon H∞ fault estimation problem for a class of nonlinear stochastic time-varying systems with both randomly occurring faults and fading channels. The system model (dynamical plant) is subject to Lipschitz-like nonlinearities and the faults occur in a random way governed by a set of Bernoulli distributed white sequences. The system measurements are transmitted through fading channels described by a modified stochastic Rice fading model. The purpose of the addressed problem is to design a time-varying fault estimator such that, in the presence of channel fading and randomly occurring faults, the influence from the exogenous disturbances onto the estimation errors is attenuated at the given level quantified by a H∞-norm in the mean square sense. By utilizing the stochastic analysis techniques, sufficient conditions are established to ensure that the dynamic system under consideration satisfies the prespecified performance constraint on the fault estimation, and then a recursive linear matrix inequality approach is employed to design the desired fault estimator gains. Simulation results demonstrate the effectiveness of the developed fault estimation design scheme.