Adaptive Extended Kalman Filter approach for Sensorless Induction Motor Drive

摘要

This paper presents sensorless control of induction motor using Adaptive Extended Kalman Filter (AEKF). The performance of EKF depends on the value of system noise covariance matrix (Q) and measurement noise covariance matrix (R). Usually (Q, R) are considered as constants, they are determined by trial-and-error method. But in fact, they change with operating conditions of Induction Motor, for this reason we should updated (Q, R) according the operating conditions. The performances have been tested by simulation using Matlab /Simulink. The Simulation results show high performances of the proposed AEKF.