报告详情
Enhancement of Low Speed Performance in Sensorless Model Predictive Control for Induction Motors
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更新：2025-04-21 14:00:05 浏览：24次
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摘要
For sensorless control systems of induction motors based on model predictive control, the motor model-based sensorless control methods suffer from low-speed regeneration instability issues, which significantly limit the low-speed operational performance of sensorless systems. To address this problem, this paper proposes an adaptive law -modified full-order observer-based model predictive control method for induction motors. First, the root cause of low-speed regeneration instability is investigated through analysis of the transfer function characteristics of the full-order observer. Second, an improved adaptive law is developed by incorporating excitation current error into the conventional speed adaptation mechanism. Finally, design of the adaptive law correction coefficients, enhanced low-speed operational characteristics are achieved. The proposed method's effectiveness in achieving stable speed estimation within the low-speed regeneration region is verified through analysis of the system and simulation.
关键词
induction motor,sensorless control,model predictive control,full-order obverser,low -speed stability
报告人
Baojia Ma
Master's Student Xi'an University of Technology稿件作者
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重要日期
-
会议日期
06月05日
2025
至06月08日
2025
-
04月30日 2025
初稿截稿日期
主办单位
IEEE PELS
IEEE
IEEE
承办单位
Southeast University
联系方式
- Quanwei Wu
- pr******@pub.seu.edu.cn
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