Speed estimation of an induction motor drive using an optimized extended Kalman filter
- 7 August 2002
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Industrial Electronics
- Vol. 49 (1), 124-133
- https://doi.org/10.1109/41.982256
Abstract
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.Keywords
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