Home Journals Articles Updates About
CN
image
收藏切换
Model Predictive Control Study of Permanent Magnet Synchronous Motor with Parameters Online Identification
收藏切换
PDF
Hai XU1, Yanqing MI2, Yanyang WANG3, Zhipeng XU4
Electric Drive | 2025, 55(2) : 3 - 12
Less
收藏切换
Electric Drive | 2025, 55(2): 3-12
Model Predictive Control Study of Permanent Magnet Synchronous Motor with Parameters Online Identification
Full
Hai XU1, Yanqing MI2, Yanyang WANG3, Zhipeng XU4
Affiliations
  • 1 Shenyang Aircraft Airworthiness Certification Center，Civil Aviation Administration of China，Shenyang 110043，Liaoning，China
  • 2 Tianjin Internal Combustion Engine Research Institute，Tianjin Motorcycle Technology Center，Tianjin 300072，China
  • 3 Aviation Weather Center，Air Traffic Management Bureau of China Civil Aviation Administration，Beijing 100018，China
  • 4 School of Automation and Information Engineering，Civil Aviation University of China，Tianjin 300300，China
Published: 2025-02-20 doi: 10.19457/j.1001-2095.dqcd25326
Outline
收藏切换

Permanent magnet synchronous motor （PMSM）has the advantages of fast dynamic response，high power density，and high torque at low speed，but the temperature variation and complex working conditions will cause the variation of PMSM parameters， thus affect motor performance and reduce the output efficiency. To address the controller parameter mismatch problem caused by the change of motor parameters in the model predictive current control，firstly an adaptive linear （Adaline）neural network was used for the online identification of the parameters of the PMSM such as inductance，flux and resistance，and then the normalized least mean square （NLMS）algorithm was introduced to improve the Adaline neural network algorithm in order to improve the convergence speed and computational accuracy of the algorithm. In addition，the high-frequency current component of the model predictive control was utilized to calculate the PMSM rotor position and the parameters of rotor angle and speed were adopt to achieve sensorless control. The experimental results show that the improved NLMS-Adaline neural network is of practical value in terms of speed and accuracy compared with recursive RLS and traditional Adaline online identification，along with a nice adaptation to parameters mismatching.

permanent magnet synchronous motor（PMSM）  /  parameter online identification  /  adaptive linear （Adaline）neural network  /  normalization  /  model predictive current control（MPCC）
Hai XU, Yanqing MI, Yanyang WANG, Zhipeng XU. Model Predictive Control Study of Permanent Magnet Synchronous Motor with Parameters Online Identification[J]. Electric Drive, 2025 , 55 (2) : 3 -12 . DOI: 10.19457/j.1001-2095.dqcd25326
Appendix
Less
Year 2025 volume 55 Issue 2
PDF
150
62
Cite this Article
BibTeX
Article Info
doi: 10.19457/j.1001-2095.dqcd25326
  • Receive Date：2023-08-25
  • Online Date：2025-10-29
  • Published：2025-02-20
Article Data
Affiliations
History
  • Received：2023-08-25
  • Revised：2023-10-20
Funding
Affiliations
    1 Shenyang Aircraft Airworthiness Certification Center，Civil Aviation Administration of China，Shenyang 110043，Liaoning，China
    2 Tianjin Internal Combustion Engine Research Institute，Tianjin Motorcycle Technology Center，Tianjin 300072，China
    3 Aviation Weather Center，Air Traffic Management Bureau of China Civil Aviation Administration，Beijing 100018，China
    4 School of Automation and Information Engineering，Civil Aviation University of China，Tianjin 300300，China
References
Share
https://castjournals.cast.org.cn/joweb/dqcd/EN/10.19457/j.1001-2095.dqcd25326
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House