Partially mode-dependent l2−l∞ filtering for discrete-time nonhomogeneous Markov jump systems with repeated scalar nonlinearities

This paper is concerned with the problem of partially mode-dependent l2−l∞ filtering for discrete-time nonhomogeneous Markov jump systems (MJSs) with repeated scalar nonlinearities. Our main purpose is to design a partially mode-dependent l2−l∞ filter such that the filtering error system is stochastically stable with l2−l∞ performance. The time-varying transition probabilities (TPs) are depicted as a polytope. By adopting the diagonally dominant Lyapunov functional and based on linear matrix inequalities (LMIs), sufficient conditions are presented for the existence of the filter. Three examples are given to validate the effectiveness of our results.