广西师范大学学报（自然科学版） ›› 2016, Vol. 34 ›› Issue (2): 21-27.doi: 10.16088/j.issn.1001-6600.2016.02.004

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基于改进粒子群算法的无刷电机模糊控制研究

王国宇, 黄植功, 戴明   

  1. 广西师范大学电子工程学院,广西桂林541004
  • 收稿日期:2015-07-20 出版日期:2016-06-25 发布日期:2018-09-14
  • 通讯作者: 黄植功(1970—),男,广西田东人,广西师范大学副教授。E-mail:hbypolly@mailbox.gxnu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(51367005)

Fuzzy Control Research for Brushless DC Motor Basedon Improved Particle Swarm Algorithm

WANG Guoyu, HUANG Zhigong, DAI Ming   

  1. College of Electronic Engineering,Guangxi Normal University,Guilin Guangxi 541004,China
  • Received:2015-07-20 Online:2016-06-25 Published:2018-09-14

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摘要： 为了解决在无刷直流电机控制系统中,PID调节器出现系统超调和稳定性差等问题,本文采用一种基于改进粒子群算法优化模糊控制器的速度控制算法,该算法融合粒子群算法和量子算法的优点。实验仿真结果表明:优化后的模糊控制器动态性能和静态性能都优于传统PID控制,具有很好的鲁棒性和控制精度。

关键词: 无刷直流电机, 模糊控制器, 粒子群, 量子算法, 改进粒子群

Abstract: To solve the problems of poor stability of the system PID for the regulator and overshoot in the brushless dc motor control system, this paper puts forward a kind of fuzzy controller based on improved particle swarm algorithm to optimize the speed of the controllable algorithm, which includes the advantages of particle swarm optimization (PSO) algorithm and the quantum algorithm. The experimental simulation results show that the dynamic and static performance of the optimized fuzzy controller is superior to that of traditional PID control. The new controller has very good robustness and control precision.

Key words: BLDCM, fuzzy control, PSO, quantum algorithm, improved particle swarm algorithm

中图分类号: 

  • TM341
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