Cross coupling control strategy of dual motors based on fuzzy feedback gain

The mathematical model of dual permanent magnet synchronous motors is formulated. In response to the issue of diminished synchronous performance during the initiation of the system and under unbalanced load circumstances in conventional cross-coupled control strategies, a fuzzy feedback gain controller is devised. This controller modifies the feedback gain in accordance with the synchronous error and its rate of change within the dual motor system, thus enhancing the synchronous performance. The simulation analysis conducted in MATLAB/Simulink validates that the proposed enhanced cross-coupled control method, which is predicated on fuzzy feedback gain, augments the system's synchronous performance both during startup and in the presence of unbalanced disturbances.

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Published
2025-06-30
DOI
https://doi.org/10.1117/12.3066848
Primary Topic
Iterative Learning Control Systems
Type
article
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article

Cross coupling control strategy of dual motors based on fuzzy feedback gain

Yingkun Zhou, Jie He, Yun Yao
Iterative Learning Control Systems
article

Cross coupling control strategy of dual motors based on fuzzy feedback gain

Yingkun Zhou, Jie He, Yun Yao
article en

Abstract

The mathematical model of dual permanent magnet synchronous motors is formulated. In response to the issue of diminished synchronous performance during the initiation of the system and under unbalanced load circumstances in conventional cross-coupled control strategies, a fuzzy feedback gain controller is devised. This controller modifies the feedback gain in accordance with the synchronous error and its rate of change within the dual motor system, thus enhancing the synchronous performance. The simulation analysis conducted in MATLAB/Simulink validates that the proposed enhanced cross-coupled control method, which is predicated on fuzzy feedback gain, augments the system's synchronous performance both during startup and in the presence of unbalanced disturbances.

Jiangsu University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 83%
Iterative Learning Control Systems
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