Fuzzy<i>H</i>_∞filtering for nonlinear Markovian jump neutral systems

Abstract

This article is concerned with the problem of H ∞ filter design for nonlinear Markovian jump neutral systems through the Takagi–Sugeno fuzzy model approach. By using a novel Markovian switched Lyapunov functional, a delay-dependent bounded real lemma (BRL) is presented in terms of linear matrix inequalities. Based on the derived BRL, both normal H ∞ filters and non-fragile H ∞ filters are designed, which guarantee that the corresponding filtering error systems are stochastically stable with a specified H ∞ performance level. A numerical example is given to demonstrate the effectiveness of the proposed approach.