Wavelet-based identification and control design for a class of nonlinear systems

In this paper, we extend the wavelet networks for identification and Hâcontrol of a class of nonlinear dynamical systems. The technique of feedback linearization, supervisory control and Hâcontrol are used to design an adaptive control law and also the parameter adaptation laws of the wavelet network are developed using a Lyapunov-based design. By some theorems, it will be proved that even in the presence of modeling errors, named network error, the stability of the overall closed-loop system and convergence of the network parameters and the boundedness of the state errors are guaranteed. The applicability of the proposed method is illustrated on a nonlinear plant by computer simulation. © World Scientific Publishing Company