Optimal nonlinear filters based on the Takagi-Sugeno fuzzy model

Treats the estimation of the output of interest for a class of nonlinear plants that admit the Takagi-Sugeno (TS) fuzzy model. Based on such a model, we propose the synthesis of a filter whose estimation error is less than a prescribed fraction of the disturbance, by measure of the Euclidean norm. We also address the optimization of the filter's performance.