基于多领导粒子策略的DMPSO算法在冷轧液压APC系统中的应用  

Applications of Multiple Leaders DMPSO in Hydraulic APC System of Cold Strip Mill

作　　者：魏立新[1] 王利平[1] 徐德树 林鹏[1] 杨景明[1] 

机构地区：[1]燕山大学工业计算机控制工程河北省重点实验室,秦皇岛066004

出　　处：《中国机械工程》2015年第23期3125-3129,共5页China Mechanical Engineering

基　　金：国家自然科学基金钢铁联合基金资助项目(U1260203);河北省高等学校创新团队领军人才培育计划资助项目(LJRC013);国家自然科学基金资助项目(61074099)

摘　　要：冷轧液压伺服位置自动控制(APC)系统中,系统参数会随着运行时间发生改变,针对系统这一特性,提出了一种基于改进动态多目标粒子群(DMPSO)算法的PID控制器参数整定策略。当系统发生变化时,该策略利用动态多目标粒子群算法的寻优能力和对环境变化的适应能力重新对PID参数进行整定和寻优。同时,针对算法存在的易于陷入局部最优和收敛速度较慢等缺陷,提出了一种基于多领导粒子策略的动态多目标粒子群算法。仿真结果表明:该控制系统对环境变化跟踪快,超调量小,调整时间短,性能明显优于传统PID控制。According to the characteristics that the parameters of cold rolling hydraulic APC sys-tem changed over time,which was a dynamic system.This paper proposed a strategy for PID control-ler parameters setting based on improved DMPSO algorithm.This strategy might set and optimize PID controller parameters in real time through the ability of dynamic multi-objective particle swarm optimization algorithm that adapted environment changes and optimized.Meanwhile,to avoid falling into local optimum and slow convergence speed,a DMPSO was put forward based on multiple leaders in guiding the particles search.Simulation results show that the control system with fast track,small overshoot and strong adaptability is better than the traditional PID control.

关 键 词：多领导粒子 动态多目标粒子群 APC 系统 PID 控制 dynamic MULTI-OBJECTIVE particle SWARM optimization(DMPSO) 

分 类 号：TG335.13[金属学及工艺—金属压力加工]