Singular Value-Based Analysis of Current Decoupling Control Effect of Permanent Magnet Synchronous Motors

The dq-axis coupling effect significantly influences the vector control performance of permanent magnet synchronous motors (PMSMs), and traditional proportional-integral (PI) control cannot control the system as desired. Extensive studies have addressed this coupling effect. However, traditional evaluation methods based on pole–zero distribution are not intuitive, which is unfavorable for engineers to select and apply decoupling strategies. This paper employed singular value analysis to assess coupling trends and magnitude–frequency characteristics of the system. In consideration of the effects of rotor speed, parameter estimation error, and digital delay, a comprehensive evaluation of controllers was conducted. This evaluation included feedforward, feedback, and internal model control (IMC) decoupling, with the analysis facilitated by singular value plots. Under the parameters chosen in this paper, the feedforward decoupling controller improves slightly in decoupling under time delay, but higher rotor speed degrades its performance more. The feedback decoupling controller worsens as the system’s overshoot rate surges from 19.4% to 33.4% under the effect of time delay, though it can decouple completely under ideal conditions. It is evident that the efficacy of all strategies is diminished in the presence of parameter estimation deviation. In contrast, the internal model decoupling controller shows better decoupling capability and stronger robustness, while its overshoot remains under 24%. The effectiveness of the proposed method was confirmed through a combination of simulations and experiments.

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Publication Details

Journal
Machines
Published
2026-09-07
DOI
https://doi.org/10.3390/machines14091021
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
0.00

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article

Singular Value-Based Analysis of Current Decoupling Control Effect of Permanent Magnet Synchronous Motors

Haoyu Zhou, J.H. Zhao, Dafang Wang, Qi Li et al.
Machines
Sensorless Control of Electric Motors
article

Singular Value-Based Analysis of Current Decoupling Control Effect of Permanent Magnet Synchronous Motors

Haoyu Zhou, J.H. Zhao, Dafang Wang, Qi Li, Pengbin Xu, Tianyi Zhang
article en

Abstract

The dq-axis coupling effect significantly influences the vector control performance of permanent magnet synchronous motors (PMSMs), and traditional proportional-integral (PI) control cannot control the system as desired. Extensive studies have addressed this coupling effect. However, traditional evaluation methods based on pole–zero distribution are not intuitive, which is unfavorable for engineers to select and apply decoupling strategies. This paper employed singular value analysis to assess coupling trends and magnitude–frequency characteristics of the system. In consideration of the effects of rotor speed, parameter estimation error, and digital delay, a comprehensive evaluation of controllers was conducted. This evaluation included feedforward, feedback, and internal model control (IMC) decoupling, with the analysis facilitated by singular value plots. Under the parameters chosen in this paper, the feedforward decoupling controller improves slightly in decoupling under time delay, but higher rotor speed degrades its performance more. The feedback decoupling controller worsens as the system’s overshoot rate surges from 19.4% to 33.4% under the effect of time delay, though it can decouple completely under ideal conditions. It is evident that the efficacy of all strategies is diminished in the presence of parameter estimation deviation. In contrast, the internal model decoupling controller shows better decoupling capability and stronger robustness, while its overshoot remains under 24%. The effectiveness of the proposed method was confirmed through a combination of simulations and experiments.

MachinesVol. 14(9)
Harbin Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 20%
Sensorless Control of Electric Motors
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