Fuzzy Robust Adaptive Control for a Class of Nonlinear Systems Represented by Input-Output Models

A fuzzy robust adaptive control design scheme is developed for a class of nonlinear system represented by input-output models with unknown nonlinear function. The control gain of the nonlinear system is unknown. By on-line approximating the unknown nonlinear functions using two Mamdani fuzzy logic systems, the proposed approach does not require the unknown parts to satisfy the linear dependence condition. It is proved that with the proposed control law and update laws, the closed-loop system is guaranteed to be stable and the tracking error converges to zero in the presence of unknown nonlinearity. A simulation example is presented to demonstrate the method.