Globally adaptive asymptotic tracking control of nonlinear systems using nonlinearly parameterized fuzzy approximator

In this paper, the problem of globally stable adaptive fuzzy tracking control is addressed for a class of uncertain nonlinear systems in the canonical form. Instead of linearly parameterized fuzzy logic system (FLS), nonlinearly parameterized FLS is used to approximate the unknown nonlinear function. By combining the new parametrization of Gaussian membership function and the signal replacement approach, a novel adaptive fuzzy controller is designed. It is shown that all signals in the closed-loop system are globally bounded and that the tracking error converges to zero asymptotically. A simulation example is included to illustrate the effectiveness of the proposed approach.