摘要
针对鲸鱼优化算法易陷入局部最优以及无刷直流电机(brushless DC motor,BLDCM)速度控制响应慢、超调量大等缺点,提出一种改进鲸鱼优化算法(improve whale optimization algorithm,IWOA)优化PID(proportional integral derivative)参数的无刷直流电机速度控制算法.该算法采用高斯变异因子、自适应权重因子和动态阈值相结合对鲸鱼优化算法进行优化.仿真实验结果表明,改进鲸鱼优化PID的无刷直流电机转速控制算法具有更快的收敛速度以及较小的超调现象,鲁棒性也更好.
Aiming at the problems that the whale optimization algorithm was prone to getting stuck in local optima and had drawbacks such as slow speed control response and large overshoot of brushless DC motor,we proposed an improved whale optimization algorithm(IWOA)for optimizing proportional integral derivative(PID)parameters in brushless DC motor speed control.The algorithm combined Gaussian mutation factor,adaptive weight factor,and dynamic threshold to optimize the whale optimization algorithm.The simulation experiment results show that the improved whale optimization PID speed control algorithm of brushless DC motor has faster convergence rate,smaller overshoot phenomenon,and better robustness.
作者
兰淼淼
胡黄水
王婷婷
王宏志
LAN Miaomiao;HU Huangshui;WANG Tingting;WANG Hongzhi(School of Computer Science&Engineering,Changchun University of Technology,Changchun 130012,China)
出处
《吉林大学学报（理学版）》
CAS
北大核心
2024年第3期704-712,共9页
Journal of Jilin University:Science Edition
基金
吉林省科技发展计划项目(批准号:20210201051GX).
作者简介
第一作者:兰淼淼(1998-),女,汉族,硕士研究生,从事电机控制的研究,E-mail:1580424330@qq.com;通信作者:胡黄水(1971-),男,汉族,博士,教授,从事无线传感器网络及轨道车辆动力学的研究,E-mail:huhs08@163.com.
