Semantic Apparatus – Sensorless adaptive rotor flux direct vector-controlled induction motor drive based on fuzzy logic control flux estimator

Cited by Lee Sonogan


Abstract by Ying-Piao Kuo, Yan-Chen Ji

In this paper, we propose the application of a speed estimation strategy to a fuzzy logic control flux estimator for a sensorless adaptive rotor flux direct-vector-controlled (RFDVC) induction motor drive. The RFDVC induction motor drive was established using the stator current and rotor flux, with the stator current being obtained from the induction motor. The model reference adaptive system (MRAS) theory was utilized to develop an adaptive rotor flux estimator based on voltage-model and current-model flux estimators. The estimated rotor speed and synchronous angle position are derived from the adaptive flux estimator. The adjustment mechanism of this estimator was designed using the fuzzy logic control strategy because this scheme is simple, easy to implement, and requires no precise information about the mathematical model. The MATLAB/SimulinkĀ® toolbox was used to simulate this system, and all the control algorithms were realized using a TI 6713-and-F2812 DSP card to validate this approach. Both the simulation and experimental results (including the estimated rotor speed, electromagnetic torque, and stator flux locus) confirmed the effectiveness of the proposed system and thereby validate the proposed approach.

Publication: Journal of Low Frequency Noise, Vibration and Active Contro (Peer-Reviewed Journal)

Pub Date: May 24, 2021 Doi:

Keywords: Sensorless, rotor flux direct vector control, model reference adaptive system, flux estimator, fuzzy logic control strategy (Plenty more sections and references in this research article)

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