Speed sensorless vector control of induction motor based on reduced order extended Kalman filter

Abstract

A vector control of induction motor, by the estimated rotor speed and rotor flux, using a new reduced-order extended Kalman filter is proposed. With this method, only the rotor flux components are selected as the state variables. The rotor speed is regarded as a parameter, and the augmented states consist of the rotor flux components and the rotor speed. The reduced-order extended Kalman filter is employed to estimate the rotor speed and rotor flux of an induction motor online by using only the stator voltage references and the measured stator currents. The estimated rotor flux is used for the field orientation and flux control, and the estimated speed is used for the overall speed control. Since the current control is performed at the synchronous rotating reference frame, the estimated rotor flux information is also used for the reference frame transformation of the current controller. The order reduction algorithm decreases the computational complexity and makes the proposed estimator technologically feasible to be implemented in real time. Computer simulations of the speed control have been carried out to test the usefulness of the estimation algorithm. The simulation results show good performance of the rotor flux and speed estimations.