Speed Control Method of Permanent Magnet Synchronous Motor optimized by Artificial Bee Colony Algorithm

Yichen Wang, E. Kang, Jian-jun He
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Abstract

This paper proposes a speed controller designed based on the principle of model predictive control, and uses an improved artificial bee colony method to adjust the controller parameters. Adding an improved artificial bee colony algorithm to the controller can avoid the tedious parameter tuning process and further improve the robustness of the controller. The controller completes the output of the control quantity in each control cycle, and uses an improved artificial bee colony algorithm to re-adjust the parameters, so that the controller's parameters are optimal under any working conditions. Simulations and experiments have proved the effectiveness of the algorithm and controller.
基于人工蜂群算法优化的永磁同步电机速度控制方法
提出了一种基于模型预测控制原理设计的速度控制器,并采用改进的人工蜂群方法对控制器参数进行调整。在控制器中加入改进的人工蜂群算法,避免了繁琐的参数整定过程,进一步提高了控制器的鲁棒性。控制器在每个控制周期内完成控制量的输出,并采用改进的人工蜂群算法对参数进行重新调整,使控制器的参数在任何工况下都是最优的。仿真和实验证明了该算法和控制器的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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