Model reference fuzzy control of nonlinear dynamical systems using an optimal observer

This paper proposes a novel indirect model reference fuzzy control approach for nonlinear systems, expressed in the form of a Takagi Sugeno (TS) fuzzy model based on an optimal observer. In contrast to what is seen in the literature on adaptive observer-based TS fuzzy control systems, the proposed method is capable of tracking a reference signal rather than just regulation. Additionally the proposed algorithm benefits from an adaptation algorithm which estimates the parameters of observer optimally. The stability analysis of the adaptation law and the controller is done using an appropriate Lyapunov function. The proposed method is then simulated on the control of Chua's circuit and it is shown that it is capable of controlling this chaotic system with high performance.