Improved filtering of interval type-2 fuzzy systems over Gilbert-Elliott channels

This study is concerned with the filtering problem for networked interval type-2 (IT2) fuzzy systems in the presence of a time-varying saturation function. Different from the existing Bernoulli-type/Gilbert-Elliott packet loss over the unreliable medium, a generalized Gilbert-Elliott model is presented to describe the data transmission follows a two-state nonhomogeneous Markov process, whose transition probabilities are time-varying. For the purpose of mitigating the impacts of abnormal information, a novel filter in the presence of saturation function is constructed, in which the saturation level is dynamically updated along with the estimation errors. On the basis of Lyapunov theory, sufficient conditions for finite-time boundedness of IT2 fuzzy systems are devised. In the end, a simulation example is exploited to show the effectiveness of the above-derived results.