A Novel Adaptive Wavelet Fuzzy Cerebellar Model Articulation Control System Design for Voice Coil Motors

In this paper, a novel adaptive wavelet fuzzy cerebellar model articulation control system is developed for the trajectory tracking control of voice coil motors (VCMs). Since the precise model of the VCM is difficult to obtain, a model-free intelligent control system is developed for the precise trajectory tracking of VCMs. This control system comprises a wavelet fuzzy cerebellar model articulation controller (CMAC) (WFCMAC) and a fuzzy compensator. The novel WFCMAC incorporates the wavelet decomposition property with a fuzzy CMAC fast learning ability, and it is used to imitate an ideal controller. This WFCMAC is a generalization network. In some special cases, it can be reduced to a fuzzy neural network (NN), a wavelet NN, and a CMAC. Moreover, the fuzzy compensator is developed to attenuate the effect of the approximation error caused by the WFCMAC approximator. The online learning algorithm of the controller's parameters is derived based on the Lyapunov function; thus, the stability of the system can be guaranteed. Finally, the developed control system is applied to the trajectory tracking control of a VCM. From the experimental results, it is verified that the proposed WFCMAC control scheme can achieve favorable tracking performance even if the system model of the VCM is unknown. Furthermore, the salient merits are also indicated in comparison with a proportional-integral-derivative controller.