基于改进粒子群算法的多电机智能控制研究  

Research on Multi-motor Intelligent Control Strategy Based on Improved Particle Swarm Algorithm

作　　者：曾宪荣[1] 吴晖辉[1] 方王进 谢凌波 ZENG Xianrong;WU Huihui;FANG Wangjin;XIE Lingbo(School of Intelligent Manufacturing,Shunde Polytechnic,Foshan Guangdong 528330,China;Foshan Eagle Vision Technology Co.,Ltd.,Foshan Guangdong 528332,China;School of Mechatronic Engineering and Automation,Foshan University,Foshan Guangdong 528300,China)

机构地区：[1]顺德职业技术学院智能制造学院,广东佛山528330 [2]广东鹰野智能科技有限公司,广东佛山528332 [3]佛山科学技术学院机电工程与自动化学院,广东佛山528300

出　　处：《机床与液压》2023年第14期75-80,共6页Machine Tool & Hydraulics

基　　金：广东省基础与应用基础研究基金项目(61573233);广东省普通高校特色创新项目(2020KTSCX365)。

摘　　要：伺服电机作为全自动线束端子组装设备驱动、控制和机械传动的主要联系环节,其控制系统的优劣决定了整个设备的性能。结合端子组装设备的结构和工作原理,对端子组装设备中重要的伺服系统建立了控制数学模型。为了得到较优的控制器参数,对粒子群算法(PSO)搜索寻优进行了改进,通过PSO对PID控制器进行参数优化,并利用优化后的PID控制器设计多电机功率平衡控制策略。仿真验证表明:改进粒子群算法能有效实现多电机功率平衡控制,在负载发生变化的情况下,控制策略能够控制每个电机的输出实现均衡分配负载。Servo motor is the main link of driving,controlling and mechanical transmission of the wire harness terminals assembly equipment,the quality of its control system determines the performance of the equipment.Combining the structure and working principle of the equipment,a control mathematical model was established for the important servo system of the equipment.In order to obtain better controller parameters,the particle swarm optimization(PSO)search optimization was improved,and the PID controller parameters were optimized through PSO,and the optimized PID controller was used to design multi-motor power balance control strategy.The simulation verification shows that the improved particle swarm algorithm can realize the multi-motor power balance control effectively,with the changing of load,the control strategy can control the output of each motor to achieve a balanced load distribution.

关 键 词：端子组装设备 粒子群算法 多机功率平衡 智能控制 

分 类 号：TM933[电气工程—电力电子与电力传动]