Adaptive Periodic Speed Fluctuation Suppression for Permanent Magnet Compressor Drives

Single-rotor compressor load torque exhibits huge periodic fluctuations, which lead to noticeable speed fluctuations. Therefore, an adaptive periodic speed fluctuation suppression method (APSFSM) based on the recursive Gauss-Newton (RGN) algorithm is proposed in this paper. The APSFSM consists of two parts: a traditional proportional-integral (PI) speed regulator is used to handle low-frequency disturbances, while the RGN part is responsible for suppressing disturbances at specific frequencies. The RGN adopts a strategy based on angle rather than time, considering the frequent speed regulation requirements of compressors, which means that it can achieve smoother speed regulation. Moreover, the RGN also has strong robustness regarding system phase shift. The compensation current of APSFSM can adaptively adjust its amplitude and phase based on real-time speed errors, maintaining the significant suppression of speed fluctuations under different operating conditions. For this paper, a series of experiments were conducted on a 650W compressor platform, and the experimental results prove the effectiveness of the proposed method.

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Publication Details

Journal
Sensors
Published
2025-03-26
DOI
https://doi.org/10.3390/s25072074
Citations
1
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
1.21
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article

Adaptive Periodic Speed Fluctuation Suppression for Permanent Magnet Compressor Drives

Jiannan Zhang, Hongda Song, Yang Yang, Chenchen Zhang et al.
1 citations
Sensors
Iterative Learning Control Systems
1.21
article

Adaptive Periodic Speed Fluctuation Suppression for Permanent Magnet Compressor Drives

Jiannan Zhang, Hongda Song, Yang Yang, Chenchen Zhang, Yibo Guo, Yimin Gong
article en
1 citations

Abstract

Single-rotor compressor load torque exhibits huge periodic fluctuations, which lead to noticeable speed fluctuations. Therefore, an adaptive periodic speed fluctuation suppression method (APSFSM) based on the recursive Gauss-Newton (RGN) algorithm is proposed in this paper. The APSFSM consists of two parts: a traditional proportional-integral (PI) speed regulator is used to handle low-frequency disturbances, while the RGN part is responsible for suppressing disturbances at specific frequencies. The RGN adopts a strategy based on angle rather than time, considering the frequent speed regulation requirements of compressors, which means that it can achieve smoother speed regulation. Moreover, the RGN also has strong robustness regarding system phase shift. The compensation current of APSFSM can adaptively adjust its amplitude and phase based on real-time speed errors, maintaining the significant suppression of speed fluctuations under different operating conditions. For this paper, a series of experiments were conducted on a 650W compressor platform, and the experimental results prove the effectiveness of the proposed method.

SensorsVol. 25(7)
Jilin University (CN)
Openalex Percentile: Top 23%
Iterative Learning Control Systems
1.21
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Adaptive Periodic Speed Fluctuation Suppression for Permanent Magnet Compressor Drives — Jiannan Zhang, Hongda Song, et al. · Sensors (2025) | TGRS Research Map | TGRS