摘要
挖掘机工作装置精确的位置控制是实现其轨迹自动控制的基础。提出一种改进粒子群优化算法,应用于液压系统PID参数的优化整定中,把遗传算法中的选择和交叉两种操作方式添加到标准的粒子群算法中形成的混合优化算法,提高了算法的搜索能力。建立具有整定PID控制器功能的仿真平台,使用改进粒子群算法、标准粒子群算法和相位裕度方法对PID控制器进行整定仿真,根据仿真结果,进行了模拟铲斗平地运动试验。仿真和试验结果表明改进粒子群算法整定的PID控制器参数,在电液伺服系统的动态响应和精确的轨迹控制方面有良好效果。
Accurate position control of excavator working device is the basis of automatic trajectory control.An improved particle swarm optimization(IPSO)algorithm is proposed,which is applied to the optimization of PID parameters in hydraulic system.The hybrid optimization algorithm is formed by adding two modes of selection and crossover in the genetic algorithm to the standard particle swarm algorithm,in order to enhance the searching efficiency.A simulation platform with the tuning PID controller function is developed,the improved particle swarm optimization(IPSO),standard particle swarm optimization(SPSO)and phase margin(PM)method are used to simulate the PID controller,according to the simulation results,the simulation of bucket flat motion is carried out.The simulation and experimental results show that the IPSO algorithm can perform well in PID control for the dynamic response and precise trajectory control of electro-hydraulic servo system.
作者
翁文文
殷晨波
冯浩
周俊静
WENG Wen-wen;YIN Chen-bo;FENG Hao;ZHOU Jun-jing(Institute of Automobile and Construction Machinery Nanjing Tech University,Jiangsu Nanjing211816,China)
出处
《机械设计与制造》
北大核心
2020年第2期166-169,共4页
Machinery Design & Manufacture
基金
江苏省科技计划项目（BY2015005-15)
关键词
位置控制
电液伺服系统
改进粒子群算法
遗传算法
Position Control
Electro-Hydraulic Servo System
Improved Particle Swarm Optimization Algorithm
Genetic Algorithm
