吉林大学学报(理学版) ›› 2020, Vol. 58 ›› Issue (6): 1421-1428.

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遗传算法优化的无刷直流电机模糊PID控制器设计

王婷婷1, 王宏志1,2, 刘清雪3, 胡黄水2, 王出航4   

  1. 1. 长春工业大学 机电工程学院, 长春 130012;2. 长春工业大学 计算机科学与工程学院, 长春 130012;
    3. 吉林建筑科技学院 计算机科学与工程学院, 长春 130114; 4. 长春师范大学 计算机科学与技术学院,  长春 130032
  • 出版日期:2020-11-18 发布日期:2020-11-26
  • 通讯作者: 刘清雪 601630419@qq.com

Design of Fuzzy PID Controller for Brushless DC Motor Optimized by GA

WANG Tingting1, WANG Hongzhi1,2, LUI Qingxue3, HU Huangshui2, WANG Chuhang4   

  1. 1. School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China;
    2. School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China;
    3. School of Computer Science and Engineering, Jilin University of Architecture and Technology, Changchun 130114, China;
    4. College of Computer Science and Technology, Changchun Normal University, Changchun 130032, China
  • Online:2020-11-18 Published:2020-11-26

摘要: 设计一种基于遗传算法优化的模糊PID(比例-积分-微分)控制器GFPC(genetic algorithm based fuzzy PID controller), 以提高无刷直流电机的工作稳定性. GFPC通过模糊控制器整定PID的比例、积分和微分系数, 并采用改进的遗传算法对模糊控制器的隶属度函数和模糊规则进行优化, 以改善无刷直流电机的控制效果. 通过对比实验对该方法进行测试, 结果表明, GFPC具有更好的稳态性能和动态品质, 且自适应能力与鲁棒性更强.

关键词: 无刷直流电机, 模糊PID控制器, 遗传算法, 隶属度函数及模糊规则

Abstract: A genetic algorithm based fuzzy PID (proportional-integral-differential) controller genetic algorithm based fuzzy PID controller (GFPC) was designed to improve the stability of brushless DC motor. GFPC used fuzzy controller to adjust the proportional, integral and differential coefficients of PID, and an improved genetic algorithm was used to optimize the membership function and fuzzy rule of fuzzy controller to improve the control effect of brushless DC motor. The method was tested by contrast experiment. The experimental results show that GFPC has good steady-state performance and dynamic quality, and has stronger adaptive ability and robustness.

Key words: brushless DC motor, fuzzy PID controller, genetic algorithm, membership function and fuzzy rule

中图分类号: 

  • TP273