基于混合粒子群算法的船用离心泵电机优化研究  

Optimization of marine centrifugal pump motor based on hybrid particle swarm optimization

作　　者：付荣赫 邢吉生[1] FU Rong-he;XING Ji-sheng(School of Electrical and Information Engineering,Beihua University,Jilin 132021,China)

机构地区：[1]北华大学电气与信息工程学院,吉林吉林132021

出　　处：《舰船科学技术》2022年第18期134-138,共5页Ship Science and Technology

基　　金：吉林省科技发展计划重点研发项目(20200403133SF,20210203109SF)。

摘　　要：在船舶系统中,离心泵在运行时起到了关键性的作用,而其驱动电机可靠运行是泵能够稳定工作的前提,传统PID手动调参方法存在整定时间长、难度大等缺点,很难达到理想的控制结果。针对以上问题,提出一种用混合粒子群算法(HPSO)来优化PID控制器参数的方法,将蝙蝠算法(BA)中随机移动概念引入到粒子群算法(PSO)中,并将其和PSO算法、传统方法进行对比分析,利用Matlab软件搭建PID控制模型。仿真结果表明,运用HPSO优化的PID控制器能够克服标准PSO算法易陷入局部极值的缺点,可以高效、精确、快速地寻优出PID控制器的最佳参数,并展现出了鲁棒性好、调节时间少、运行相对稳定等优点。In the marine system, the centrifugal pump plays a key role in operation, and whether the driving motor runs reliably is the premise for the pump to work stably. The traditional PID manual parameter adjustment method has the disadvantages of long setting time and great difficulty, so it is difficult to achieve the ideal control results. To solve the above problems, a method of using hybrid particle swarm optimization(HPSO) to optimize the parameters of PID controller is proposed. The concept of random movement in bat algorithm(BA) is introduced into particle swarm optimization algorithm,which is compared with PSO algorithm and traditional methods, and the PID control model is established by MATLAB software. The simulation results show that the PID controller optimized by HPSO can overcome the disadvantage that the traditional particle swarm optimization(PSO) is easy to fall into local optimization, and can find the best parameters of the PID controller efficiently, accurately and quickly. It shows the advantages of good robustness, less adjustment time and relatively stable operation, and the system can run more stably.

关 键 词：PID控制器 混合粒子群算法 参数优化 离心泵电机 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]