$H_{\bm \infty}$ Fuzzy Filtering of Nonlinear Systems With Intermittent Measurements

Abstract

This paper is concerned with the problem of H _infin fuzzy filtering of nonlinear systems with intermittent measurements. The nonlinear plant is represented by a Takagi-Sugeno (T-S) fuzzy model. The measurements transmission from the plant to the filter is assumed to be imperfect, and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the phenomenon of the missing measurements. Attention is focused on the design of an H _infin filter such that the filter error system is stochastically stable and preserves a guaranteed H _infin performance. A basis-dependent Lyapunov function approach is developed to design the H _infin filter. By introducing some slack matrix variables, the coupling between the Lyapunov matrix and the system matrices is eliminated, which greatly facilitates the filter-design procedure. The developed theoretical results are in the form of linear matrix inequalities (LMIs). Finally, an illustrative example is provided to show the effectiveness of the proposed approach.