Paper Title
Study on a New and Effective Direct De-Coupling Controller for Induction Motors Applying Full Stage Feedback Linearization Algorithm, Kalman Filter and Adaptive Backstepping Technology

Abstract
Induction Motors are usually expressed by complicated non-linear models due to their non-linear nature. In this paper, a new and effective method for modeling stator current and estimating rotor flux of induction motors has been developed by applying Direct–Decoupling Methodology. A nonlinear control approach with full state feedback linearization has been used to construct the decoupling form of the induction motors. A new current controller named “directdecoupling”, based on exact linearization algorithm of the motor current model has been proposed. The obtained linear system in a new state-space is very convenient to design the current controller and the rotor flux estimator for induction motors. A linear Kalman filter has also been derived to construct an observer for rotor flux. Effectiveness of the new adaptive backstepping controller for induction motors and Kalman filter for observation of rotor flux has been verified by simulations and experiments in wide ranges of motor speed. Simulations and experiment results show clearly that the rotor flux can be well estimated in all operating conditions and performance of induction motors under all dynamic modes can be improved by using the new developed controller. Keywords- Adaptive Control, Backstepping, Direct-Decoupling, Induction Motors, Kalman Filter, Non-linear control.