Nonlinearity Compensation in Inverters and PMSMs Using an Artificial Neural Network

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초록

This paper proposes a compensation method for voltage distortion caused by inverter nonlinearities and distortion induced by the permanent magnet synchronous motors (PMSMs). To mitigate distortions caused by both the inverter and the motor, a compensation voltage was modeled. Since the shape of compensation voltage is difficult to describe theoretically, an Artificial Neural Network (ANN) was used to represent it. The proposed ANN model compensates for the nonlinearities of both the inverter and the PMSMs, resulting in the reduction of 6th-order harmonic current components. The validity of the proposed method is experimentally verified using a PMSM with the back electromotive force (back-EMF) that includes 5th-and 7th-order harmonic components.

키워드

PMSMsArtificial Neural NetworkHarmonic ControlInverter NonlinearityMotor Nonlinearity
제목
Nonlinearity Compensation in Inverters and PMSMs Using an Artificial Neural Network
저자
Kang, Chan-HwiKim, Na-GyeongJin, Dong-SupYoon, Young-Doo
DOI
10.1109/SLED63792.2025.11154777
발행일
2025-09
유형
Proceedings Paper
저널명
2025 IEEE 12TH INTERNATIONAL SYMPOSIUM ON SENSORLESS CONTROL FOR ELECTRICAL DRIVES, SLED
2025
페이지
1 ~ 6