In this paper we are interested in an indirect fuzzy adaptive control of SISO nonlinear systems in the presence of parametric uncertainties. The plant model structure is represented by a fuzzy system. The essential idea of the on-line parametric estimation of the plant model is based on a comparison of the measured state with the estimate one. The design of adaptive law is based on a Lyapunov approach. The control action comprises two terms: a classical indirect adaptive fuzzy controller and a supervisory controller. The plant state tracks asymptotically any bounded reference input signal. Two examples are used to check performance of the proposed controller.
Nonlinear system; Fuzzy system; State estimation; Adaptive fuzzy control; Stability; Supervisory control; Tracking error.
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