基于杂交PSO算法的直线电机伺服参数优化  

Servo Parameters Optimization of Linear Motor Based on Hybrid-PSO Algorithm

作　　者：王志昊 Wang Zhihao(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学机械工程学院,上海市200093

出　　处：《农业装备与车辆工程》2022年第3期57-61,共5页Agricultural Equipment & Vehicle Engineering

摘　　要：伺服参数整定是影响直线电机系统控制性能优劣的关键因素,针对其参数难以整定的问题,提出一种基于杂交PSO算法的解决方案。通过引入粒子杂交操作,有效增强算法对最优参数的全局搜索能力,并且其收敛速度和精度得到提升。仿真结果表明,应用杂交PSO算法对电机系统数学模型的伺服参数进行整定优化效果明显。对比标准粒子群算法与文献改进粒子群算法,优化后的伺服控制系统对阶跃响应的超调量减少31.34%,上升时间、调整时间明显缩短,并且系统在应对输入突变时表现出较好的跟踪性能。Servo parameter tuning is a key factor that affects the control performance of the linear motor system.Aiming to tuning its parameters,this paper proposes a solution based on the Hybrid-PSO algorithm.By introducing the particle hybridization operation,the algorithm's global search ability for optimal parameters is effectively enhanced,and its convergence speed and accuracy are improved obviously.The simulation results show that the application of Hybrid-PSO algorithm to tuning and optimizing the servo parameters of the mathematical model of the motor system makes effective improvements.Comparing the standard PSO and proposed literature-improved-PSO,after the optimization of this scheme,the servo control system's step response overshoot is reduced by 31.34%,the rise time and adjustment time are significantly shortened,and the system shows greater tracking performance in response to sudden changes in input.

关 键 词：改进PSO 杂交算子 直线电机 伺服参数优化 PID整定 

分 类 号：TM359.4[电气工程—电机]