Optimized Kalman filters for sensorless vector control induction motor drives

<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and extended (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF EKF depends on accurate selection state noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find optimal values main objectives be minimized are mean square errors (MSE) actual estimation speed, current, flux. Simulation results show matrices can improve torque, flux in DFOCIM Furthermore, present higher than under different operating conditions.</span>