Research on Current Harmonic Suppression Method for Dual Three-Phase Permanent Magnet Synchronous Motor Based on Fuzzy Dynamic Gain Repetitive Control

Regarding the problems of fifth and seventh order characteristic harmonics existing in the operation of the dual three-phase permanent magnet synchronous motor, repetitive control is often used to improve the steady-state accuracy. However, traditional RC mostly adopts a fixed forward-learning gain and is set through trial-and-error methods, which requires a lot of time. Therefore, this paper proposes an improved repetitive control strategy based on fuzzy dynamic gain scheduling. This strategy precisely extracts the comprehensive distortion characteristic values of the target suppressed harmonics and the warning harmonics online; it designs a fuzzy adaptive adjustment mechanism to actively increase the gain to achieve rapid suppression when the target harmonic is severe, and rapidly reduce the gain to ensure the safety of operation when a low-frequency oscillation trend is detected. Simulation results show that the proposed method effectively reduces the total harmonic distortion of the current while maintaining the stability of the system and improves the harmonic suppression accuracy.

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Publication Details

Journal
Electronics
Published
2026-04-13
DOI
https://doi.org/10.3390/electronics15081623
Primary Topic
Iterative Learning Control Systems
Type
article
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article

Research on Current Harmonic Suppression Method for Dual Three-Phase Permanent Magnet Synchronous Motor Based on Fuzzy Dynamic Gain Repetitive Control

Peng Zhu, Yuxin Niu, Shukai Lu
Electronics
Iterative Learning Control Systems
article

Research on Current Harmonic Suppression Method for Dual Three-Phase Permanent Magnet Synchronous Motor Based on Fuzzy Dynamic Gain Repetitive Control

Peng Zhu, Yuxin Niu, Shukai Lu
article en

Abstract

Regarding the problems of fifth and seventh order characteristic harmonics existing in the operation of the dual three-phase permanent magnet synchronous motor, repetitive control is often used to improve the steady-state accuracy. However, traditional RC mostly adopts a fixed forward-learning gain and is set through trial-and-error methods, which requires a lot of time. Therefore, this paper proposes an improved repetitive control strategy based on fuzzy dynamic gain scheduling. This strategy precisely extracts the comprehensive distortion characteristic values of the target suppressed harmonics and the warning harmonics online; it designs a fuzzy adaptive adjustment mechanism to actively increase the gain to achieve rapid suppression when the target harmonic is severe, and rapidly reduce the gain to ensure the safety of operation when a low-frequency oscillation trend is detected. Simulation results show that the proposed method effectively reduces the total harmonic distortion of the current while maintaining the stability of the system and improves the harmonic suppression accuracy.

ElectronicsVol. 15(8)
Naval University of Engineering (CN)
Affordable and clean energy
Openalex Percentile: Top 15%
Iterative Learning Control Systems
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