H∞ state estimation for discrete-time systems with fading measurements and randomly varying nonlinearities

In this paper, the H_∞ state estimation problem is investigated for a class of stochastic systems with the simultaneous presence of fading measurements and randomly varying nonlinearities (RVNs). A sequence of random variables obeying the Bernoulli distribution is utilized to govern RVNs. The Rice fading model, simultaneously, is employed to describe the phenomena of channel fadings by setting different values of the channel coefficients. The purpose of this paper is to design an H_∞ state estimator such that the augmented system is stochastically stable and the disturbance rejection attenuation is constrained to a given level by means of the H_∞-performance index. In terms of stochastic analysis methods, sufficient conditions are established under which the addressed state estimation problem is recast as solving a convex optimization problem via the semi-definite programme method. Finally, a simulation example is employed to show the usefulness of the proposed design scheme.