Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag

Abstract

Due to sensor limitations in some applications, induction motors state estimators are widely used in industries. One of the most powerful tools available for estimation is the Kalman filter. In this paper, unscented Kalman filter (UKF) and extended Kalman filter (EKF) is used to estimate the speed and torque of an induction motor. In the UKF algorithm, three types of unscented transformation (UT): basic, general and spherical types are presented and compared. It will be shown that the spherical UKF presents good estimation performance. Speed and torque Estimation approach is applied at both steady state conditions and at the time of sudden and rapid change in the motor input voltage. It will be shown that, EKF cannot trace the motor speed at the time of a large disturbance. Finally, experimental validation is presented to show the effectiveness of UKF for continuous estimation of torque and speed of induction motors.