Adaptive type-2 fuzzy control for induction motor

This paper proposes a new indirect adaptive fuzzy controller based on interval type-2 fuzzy logic systems for indirect vector controlled induction motor drive. Type-2 fuzzy controller compared with type-1 fuzzy controller, has the advantage that it can take into account the linguistic uncertainties present in the rules of the estimated models. The proposed control scheme consists of a combination of two controllers: a type-2 fuzzy controller and a supervisory controller. The supervisory controller is used when the system loop tend to be unstable. The tuning parameters for the type-2 fuzzy controller will change according to some learning algorithms based on Lyapunov theorem.