Robust State Estimation for T–S Fuzzy Markov Jump Systems

The problem of robust state estimation for a class uncertain nonlinear systems with Markov jump is investigated. system under consideration represented by the Takagi–Sugeno (T–S) fuzzy model because it difficult to describe. Firstly, different from traditional T–S modeling method, deviation linear approaching considered, which as error in modeling. Secondly, through method based on sensitivity penalty, we develop estimator subsystems, and obtained rules. Thirdly, stability boundedness are proved assumption conditions ensure reliability estimator. Finally, some numerical examples given verify effectiveness