State Estimation of Fuzzy Sugeno Systems with Local Nonlinear Rules and Unmeasurable Premise Variables

This paper considers the design of observers for a class of continuous and discrete-time nonlinear systems presented by Takagi-Sugeno (T-S) model with nonlinear subsystems and unmeasurable premise variables. As a result, the proposed T-S structure reduces the number of rules in the Sugeno model by using local nonlinear rules. Moreover, it can represent larger class of nonlinear systems as compared to the measurable premise variable case. The proposed observer guarantees exponential convergence of state estimation error by Lyapunov stability analysis and linear matrix inequality (LMI) formulation. Numerical examples illustrate effectiveness of the proposed method.