Direct torque fuzzy controlled induction machine drive using an optimized extended Kalman filter

In this paper, we propose an approach for improving direct torque control (DTC) of induction machines based on the theory of fuzzy logic that replaces the conventional comparators and the selection table, to reduce the torque ripples electromagnetic flux and the stator current. Then we present a speed estimator, based on the algorithm of the extended Kalman filter (EKF). The function of filtering consists to estimate the useful information which is polluted by a noise. The extended Kalman filter (EKF) aims to estimate optimally the state of linear system: this state corresponds to useful information. Before defining the optimality factors that will calculate the Kalman filter, which is in fact a stochastic criterion.. The validity of the proposed methods is confirmed by the simulation results.