ADRC Parameter Tuning of PMSM Based on Improved ChOA Algorithm
ID:164 View Protection:ATTENDEE Updated Time:2025-11-03 11:39:17 Hits:517 Poster Presentation

Start Time:2025-11-09 09:00(Asia/Shanghai)

Duration:1min

Session:P Poster presentation » P77.Electric Machine Design and Control

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Abstract
At present, proportional-integral-differential (PID) based drive system is dominiant in the control of permanent magnet synchronous motor (PMSM). However, it faces challenges in disturbance rejection ability and multi-condition robustness. A nonlinear active disturbance rejection controller (ADRC) is designed and applied to replace the traditional PID controller in the speed loop to build a speed control system based on the vector control strategy. In order to simplify the complicated tuning process and reduce the reliance on the work experience of engineers, a recently developed optimization algorithm is applied and its improved form is proposed to realize parameters tuning of the whole drive system. The immigration strategy and the fitness noise strategy are introduced to avoid falling into the local optimal solution. Through simulation, particle swarm optimization algorithm (PSO), gray wolf optimization algorithm (GWO) and traditional chimpanzee optimization algorithm (ChOA) are compared, and the results show that the proposed method performs better.
Keywords
Intelligent optimization algorithm, parameter tuning, ADRC, PMSM, ChOA
Speaker
Pengcheng Hu
Xi’an Jiaotong-Liverpool University

Submission Author
Pengcheng Hu Xi’an Jiaotong-Liverpool University
Chengcheng Xu Xi’an Jiaotong-Liverpool University
Yunfei Xie Xi’an Jiaotong-Liverpool University
Xuchen Wang Xi’an Jiaotong-Liverpool University
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Important Date
  • Conference Date

    Nov 07

    2025

    to

    Nov 09

    2025

  • Oct 30 2025

    Draft paper submission deadline

  • Nov 10 2025

    Registration deadline

Sponsored By
IEEE西南交通大学IAS学生分会
Organized By
西南交通大学电气工程学院
SPACI车网关系研究室
四川大学电力系统稳定与高压直流输电研究团队