Speed estimation of an induction motor drive using an optimizedextended Kalman filter
Shi, K.L.; Chan, T.F.; Wong, Y.K.; Ho, S.L.
Industrial Electronics, IEEE Transactions on
Volume 49, Issue 1, Feb 2002 Page(s):124 - 133
Digital Object Identifier   10.1109/41.982256
Summary:This paper presents a novel method to achieve good performance of an extended Kalman filter (EKF) for speed estimation of an induction motor drive. A real-coded genetic algorithm (GA) is used to optimize the noise covariance and weight matrices of the EKF, thereby ensuring filter stability and accuracy in speed estimation. Simulation studies on a constant V/Hz controller and a field-oriented controller (FOC) under various operating conditions demonstrate the efficacy of the proposed method. The experimental system consists of a prototype digital-signal-processor-based FOC induction motor drive with hardware facilities for acquiring the speed, voltage, and current signals to a PC. Experiments comprising offline GA training and verification phases are presented to validate the performance of the optimized EKF

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