Fuzzy supervisor based multiple model adaptive controller for systems with uncertain parameters

This paper presents a kind of multiple model adaptive controller based on fuzzy supervisor for the control system of robots with uncertain parameters. The controller uses the structure of model reference control system and adopts a fuzzy supervisor who controls the switching of respective control models instead of tuning dynamically the parameters of controller to tune control input. So a lot of calculations are avoided for tuning the parameters of controller dynamically and the dynamic response characteristics of common multiple model adaptive controller are optimized. Also performance of the whole system is improved by using the optimization based GA. Simulation results are shown to demonstrate the effectiveness of that this kind of control scheme.