In this paper, an adaptive fuzzy wavelet neural network control (AFWNNC) system, which is composed of a neural controller and an exponential compensator, is developed and presented for control of the voice coil motors. The neural controller utilizes a fuzzy wavelet neural network (FWNN) to on-line approximate an unknown nonlinear term in the system dynamics and the exponential compensator is designed to ensure the system stability of closed-loop system. Meanwhile, the parameter learning of the AFWNNC system is derived by the Lyapunov stability theory. Finally, the experiment is performed using a low-cost microcontroller to verify the design performance over a wide range of operating conditions. The experimental results show that the AFWNNC system can achieve favorable control performance due to the FWNN has the admirable property of high learning accuracy.
