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Sensors and Materials, Volume 32, Number 1(2) (2020)
Copyright(C) MYU K.K.
pp. 239-252
S&M2098 Research Paper of Special Issue
Published: January 20, 2020

Speed Estimation Direct Stator Field-orientation-controlled Induction Motor Drive Using Adaptive Flux Estimator [PDF]

Yung-Chang Luo, Bo-Wei Chen, Wen-Cheng Pu, and Neng-Sheng Pai

(Received July 23, 2019; Accepted October 4, 2019)

Keywords: speed estimation, flux estimator, current sensor, fuzzy logic control (FLC) strategy, model reference adaptive system (MRAS)

In this study, a speed estimation scheme using the fuzzy logic control (FLC) strategy adaptive flux estimator is presented for a direct stator field-orientation-controlled (DSFOC) induction motor (IM) drive. The current and flux of the stator were utilized to establish the DSFOC IM drive, and the stator current was obtained from the IM by utilizing Hall effect current sensors. The adaptive stator flux estimator was developed according to the voltage-model and current-model stator flux estimators, and the estimated rotor speed was derived from this flux estimator. The adaptation mechanism of the adaptive stator flux estimator was designed using the FLC strategy. The synchronous position angle for the coordinate transformation between the stationary and synchronous reference coordinate frames was developed using the model reference adaptive system (MRAS) based on the reactive power of an IM. The MATLAB\Simulink® toolbox was used to simulate this system, and all the control algorithms were realized using a 32-bit RX62T microcontroller to validate this approach. Both simulation and experimental results (including the estimated rotor speed, electromagnetic torque, and stator flux locus) confirmed the effectiveness of the proposed system and validated the proposed approach.

Corresponding author: Yung-Chang Luo

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Cite this article
Yung-Chang Luo, Bo-Wei Chen, Wen-Cheng Pu, and Neng-Sheng Pai, Speed Estimation Direct Stator Field-orientation-controlled Induction Motor Drive Using Adaptive Flux Estimator, Sens. Mater., Vol. 32, No. 1, 2020, p. 239-252.

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