The auxiliary CMAC applied to online tuning robust fuzzy controllers

A novel auxiliary CMAC robust fuzzy control schemes is proposed in this paper. There are two structures in the proposed schemes: one is the robust fuzzy controller and the other is the auxiliary CMAC learning algorithm. The robust fuzzy controller can achieve a certain goal without concern for instability of the controlled system in the presence of significant plant uncertainties, if the nominal parameter is roughly estimated. In order to improve the performance of robust fuzzy controller, the nominal parameter should be adjusted. Thus, an auxiliary CMAC learning algorithm under the robust fuzzy control structure is employed to online tuning the nominal parameter. Finally, simulation results demonstrate the excellent capability of the proposed structure for improving the output performance.