永磁同步电机的改进对角递归神经网络PI控制策略

Xi Wei Peng*, Han Lin Gao

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

For the problem that the permanent magnet synchronous motor AC servo system with traditional PI controller cannot strike a balance between good response performance and strong robustness, a control algorithm combining diagonal recurrent neural network (DRNN) and PI control was proposed. In addition, the idea of dynamic adjustment of the learning rate was introduced to improve the algorithm, which solves the problem that the DRNN algorithm cannot strike a balance between system stability and fast learning rate. The simulation model was constructed, and the comparison experiment between PI controller, DRNN-PI controller with fixed learning rate and DRNN-PI controller with variable learning rate was carried out. The experiment shows that the AC servo system using DRNN-PI controller with variable learning rate has a good speed performance. There is no overshoot in the speed curve, and the speed is not affected by load fluctuation.

投稿的翻译标题Improved diagonal recursion neural network and PI control of permanent magnet synchronous motor
源语言繁体中文
页(从-至)126-132
页数7
期刊Dianji yu Kongzhi Xuebao/Electric Machines and Control
23
4
DOI
出版状态已出版 - 1 4月 2019

关键词

  • Computer simulation
  • Neural nets
  • PI
  • Permanent magnet synchronous motor
  • Servo systems

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引用此

Peng, X. W., & Gao, H. L. (2019). 永磁同步电机的改进对角递归神经网络PI控制策略. Dianji yu Kongzhi Xuebao/Electric Machines and Control, 23(4), 126-132. https://doi.org/10.15938/j.emc.2019.04.016