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|Title:||Speed estimation of an induction motor drive using an optimized extended Kalman filter|
Chan, T. F.
|Source:||IEEE transactions on industrial electronics, Feb. 2002, v. 49, no. 1, p. 124-133.|
|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.|
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|Appears in Collections:||EE Journal/Magazine Articles|
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