Hybrid adaptive fuzzy controllers of robot manipulators

Abstract

A hybrid adaptive fuzzy controller comprises a weighted combination of a direct and an indirect adaptive fuzzy controllers, with a continuously-switched supervisory controller. The direct and indirect adaptive fuzzy controllers allow fuzzy control rules and fuzzy descriptions to be incorporated respectively, to achieve better adaptation speed. The choice of the weights depends on the relative importance and reliability of the available fuzzy control rules and fuzzy descriptions. Theoretical results and simulation studies on a two-link manipulator show that the proposed hybrid adaptive fuzzy controller is robust and stable. It also outperforms previous direct and indirect adaptive fuzzy controllers in terms of tracking accuracy and magnitude of control torque required.