Adaptive direct fuzzy control of SISO nonlinear systems using a fuzzy reference model

This study presents a novel fuzzy adaptive controller comprising a fuzzy direct model reference mechanism to control uncertain nonlinear SISO systems. The proposed method benefits from a reference model which is itself fuzzy. Since the reference model is fuzzy it has more degrees of freedom to define a more appropriate dynamic behavior for the system to be controlled. The flexibility caused by the fuzzy reference model makes it possible for the system to outperform the case when the reference signal is linear in terms of rise time and settling time. In addition, using the proposed approach, tracking error of the reference system reduces significantly. The direct method of Lyapunov is used to prove the stability of the system. The proposed method is tested on a Duffing oscillator subject to disturbances.