A Reference Model Based Adaptive Fuzzy Controller for Nonlinear Dynamic Systems

In this paper, we first present some dynamic TS fuzzy subsystems to approximate a nonlinear system. To make the subsystems asymptotically stable, the reference model with the same fuzzy sets of the system rule is established. A feedback controller is designed based on an exact approximation model. The control gain can be solved by LMI approach. Since in practical plant, there are parameters uncertainty and external disturbance in approximation models, we propose a new controller with an adaptive fuzzy control term to compensate the uncertainty and alleviate the disturbance. Lyapunov constitute techniques can prove the stability of the closed loop systems. The simulations results illustrate the effectiveness of this approach.