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This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components...
This paper proposes to use a differential evolution (DE) algorithm to obtain the optimal covariance matrices of a new reduced delayed-state Kalman filter (DSKF) based algorithm to realize sensorless induction motor drives. We propose to use a novel simple stator flux oriented-sliding mode (SFOSM) control scheme in conjunction with the optimized DSKF-based algorithm, estimating the stator flux linkage...
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