基于改进粒子群算法的活套系统解耦控制研究（英文）  

Research on decoupling control for looper system based on improved PSO

作　　者：周建新 姚怡兰 

机构地区：[1]华北理工大学电气工程学院,河北唐山063000

出　　处：《机床与液压》2017年第24期126-131,共6页Machine Tool & Hydraulics

基　　金：supported by Key project of Hebei Education Department(ZD2015059)

摘　　要：为了进一步提高热连轧厂的自动厚度控制精度和带钢产品质量,对活套高度和张力的耦合控制系统,建立适当的数学模型,基于耦合过程分析和实际的数据得出相对完整的活套系统的传递函数。针对活套系统所具有的非线性、强耦合、不确定性等特点,利用变异机制和粒子群算法相结合的基础上提出一种用改进的粒子群算法来优化PID神经元网络以实现对活套系统的多变量解耦控制。仿真结果表明:与传统的PID解耦控制相比较,可以获得相对更好的控制效果。In order to further improve the strip＇ s accuracy and production quality of the hot strip rolling mill, it is necessary to establish appropriate mathematical model and transferring functions of looper system on the basis of coupling process analysis and the practical data. A looper system has the features of nonlinearity, strong coupling, uncertainty, and multi-constraints. Hence, an improved particle swarm optimization algorithm was proposed based on mutation mechanism and particle swarm optimization algorithm in this paper. The PID neural network, trained by improved particle swarm optimization algorithm, was applied to decouple the looper system. The simulation re- suits showed that the algorithm has better control effect than conventional PID control system.

关 键 词：活套系统 解耦控制 PID神经元网络 自适应变异粒子群算法 

分 类 号：TH186[机械工程—机械制造及自动化]