Application of an extended Kalman filter to rotor speed and resistance estimation in induction motor vector control

Abstract

The vector control method allows high performance control of torque and speed to be achieved from an induction machine. The decoupling of the flux and the electromagnetic torque, obtained by field orientation, depends on the precision and the accuracy of the estimated states. This paper presents the application of the extended Kalman filter (EKF) to the online estimation of the rotor resistance, electrical speed and flux components. The EKF algorithm combines information from the process or the plant model with output measurements to produce an optimal estimate of the unmeasured states. The estimation of the rotor speed allows the implementation of sensorless control.