A Robust Fuzzy Observer-Based Control with Reference State Model and Unmeasurable Premise Variables: Application to a Biological Process

This paper proposes a new procedure for the design of a robust fuzzy observer-based tracking controller for nonlinear systems using Takagi-Sugeno (TS) formalism. A reference state model is considered and the premise variables are considered inaccessible to measurement. In order to ensure the global stability and to minimize efficiently the effect of the disturbance affecting the tracking performances of the closed loop system and the observer, in addition to the Lyapunov approach, the H _infinity norm is used. The controller and the observer design are developed in a single step and new sufficient conditions are obtained and given in terms of linear matrix inequalities (LMIs). The application on a biological process in simulation studies is provided to explain the tracking control design procedure and to prove the efficiency of the proposed approach.