Robust Adaptive Deadbeat Predictive Current Control of PMSM Drives based on Improved Generalized Extended State Observer

The control accuracy of conventional DPCC is greatly dependent on the parameter accuracy of the system. To overcome this limitation, a robust adaptive deadbeat predictive current control strategy based on an improved generalized extended state observer (IGESO) is proposed. This approach employs a model reference adaptive system (MRAS) to perform online identification of inductance parameters, enabling real-time updates to both the controller and IGESO to adapt to inductance variations. Furthermore, the proposed IGESO exhibits superior anti-interference and anti-noise capabilities, effectively mitigating the effects of resistance and flux parameter changes on system performance. Simulation results confirm that the proposed algorithm can effectively reduce current harmonics under parameter mismatch, showing excellent robustness and control performance.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/precede63178.2025.11130956
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00

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article

Robust Adaptive Deadbeat Predictive Current Control of PMSM Drives based on Improved Generalized Extended State Observer

Wenjie Li, Yongting Deng, Laixiang Xu, Haiyang Cao et al.
Power Systems and Renewable Energy
article

Robust Adaptive Deadbeat Predictive Current Control of PMSM Drives based on Improved Generalized Extended State Observer

Wenjie Li, Yongting Deng, Laixiang Xu, Haiyang Cao, Xiufeng Liu, Chuanlong Zhai
article en

Abstract

The control accuracy of conventional DPCC is greatly dependent on the parameter accuracy of the system. To overcome this limitation, a robust adaptive deadbeat predictive current control strategy based on an improved generalized extended state observer (IGESO) is proposed. This approach employs a model reference adaptive system (MRAS) to perform online identification of inductance parameters, enabling real-time updates to both the controller and IGESO to adapt to inductance variations. Furthermore, the proposed IGESO exhibits superior anti-interference and anti-noise capabilities, effectively mitigating the effects of resistance and flux parameter changes on system performance. Simulation results confirm that the proposed algorithm can effectively reduce current harmonics under parameter mismatch, showing excellent robustness and control performance.

Changchun Institute of Optics, Fine Mechanics and Physics (CN)
National Natural Science Foundation of China, Youth Innovation Promotion Association of the Chinese Academy of Sciences
Openalex Percentile: Top 76%
Power Systems and Renewable Energy
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