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Nonlinearity Compensation in Inverters and PMSMs Using an Artificial Neural Network

Authors
Kang, Chan-HwiKim, Na-GyeongJin, Dong-SupYoon, Young-Doo
Issue Date
Sep-2025
Publisher
IEEE
Keywords
PMSMs; Artificial Neural Network; Harmonic Control; Inverter Nonlinearity; Motor Nonlinearity
Citation
2025 IEEE 12TH INTERNATIONAL SYMPOSIUM ON SENSORLESS CONTROL FOR ELECTRICAL DRIVES, SLED, no.2025, pp 1 - 6
Pages
6
Journal Title
2025 IEEE 12TH INTERNATIONAL SYMPOSIUM ON SENSORLESS CONTROL FOR ELECTRICAL DRIVES, SLED
Number
2025
Start Page
1
End Page
6
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/210645
DOI
10.1109/SLED63792.2025.11154777
ISSN
2166-6725
2166-6733
Abstract
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.
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