This study presents a novel direct model reference fuzzy controller. It relaxes the special conditions on the reference model that is required by some of the approaches described in the literature, as well as covering a more general class of Takagi-Sugeno (T-S) systems. The stability of the proposed method is proved using a proper Lyapunov function. In addition, the effects of modeling errors on the proposed controller are considered, and a robust modification algorithm to alleviate this problem is introduced and analyzed. The proposed method is then simulated on a flexible joint robot in a feedback linearization form and on Chuas chaotic electrical circuit. Finally, it is implemented and tested on a nonlinear dc motor with nonlinear state-dependent disturbance.
- Fuzzy control
- model reference adaptive control
- Takagi-Sugeno (T-S) fuzzy model