SOA在音圈电机控制系统中应用仿真研究  

Application Simulation of SOA in Voice Coil Motor Control System

作　　者：王国龙 白端元[1] 王愚 刘云清[1] WANG Guo-long;BAI Duan-yuan;WANG Yu;LIU Yun-qing(School of Electronic Information Engineering,Changchun University of Science and Technology,Changchun Jilin 130022,China)

机构地区：[1]长春理工大学电子信息工程学院,吉林长春130022

出　　处：《计算机仿真》2023年第4期277-281,共5页Computer Simulation

基　　金：吉林省发展和改革委员会项目(2020C023-1);吉林省发展和改革委员会项目(2018C035-3);长春理工大学青年基金项目(201915010011)。

摘　　要：针对传统的PID参数整定方法存在对音圈电机控制精度不足以及响应速度慢等问题,提出了基于人群搜索算法(SOA)快速寻找音圈电机最佳PID控制参数。选取音圈电机的数学模型作为被控对象,利用SOA算法随机生成初始搜寻者并将搜寻者个体的位置参数依次赋给PID控制参数,并计算音圈电机系统的性能指标,再通过循环迭代更新搜寻者的位置直到满足系统期望指标为止。仿真结果表明,相比于粒子群算法(PSO)、遗传算法(GA),SOA算法能够有效减小系统的超调量并缩短调节时间,同时具有一定的抗干扰能力,在音圈电机控制系统中具有一定的应用价值。Aiming at the problems of insufficient control accuracy and slow response speed of voice coil motor in the traditional PID parameter tuning method,the seeker optimization algorithm(SOA)to quickly find the optimal PID control parameters of voice coil motor is proposed.The mathematical model of the voice coil motor is selected as the controlled object,the initial searcher is randomly generated by SOA,and the position parameters of the searcher are assigned to PID control parameters to calculate the performance index of the voice coil motor system,and then the position of the searcher is updated by cycle iteration until the expected index is met.The simulation results show that compared with particle swarm optimization(PSO)and genetic algorithms(GA),SOA can effectively reduce the overshoot of the system and shorten the adjustment time,and has a certain anti-interference ability,which has a certain application value in the voice coil motor control system.

关 键 词：人群搜索算法 音圈电机 应用仿真 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]