基于RBF-NN逆系统的卷取张力控制  

Control Strategy for Coiling Tension Based on RBF-Neural Network Inverse System

作　　者：蒋泽义[1] 莫天生[2] 张超[3] 

机构地区：[1]马鞍山钢铁股份有限公司煤焦化分公司,安徽马鞍山243000 [2]马鞍山钢铁股份有限公司第三钢轧厂,安徽马鞍山243000 [3]河南机电高等专科学校自动控制系,河南新乡453002

出　　处：《科技导报》2011年第23期70-73,共4页Science & Technology Review

摘　　要：基于对卷取机张力间接控制过程的研究,以提高恒张力卷取控制精度为目的,引入径向基函数(RBF)神经网络及逆系统控制理论知识,结合卷取张力控制过程的物理特性,建立了张力控制逆系统模型,其仿真结果较为理想,对实际的生产有指导意义。Based on the research on coiling tension indirect control process, for the purpose to improve the accuracy of the constant tension take-up control, RBF neural networks and inverse system control theory are introduced. The physical characteristics of coiling tension control process are combined with, an inverse system model is established, and the simulation results are satisfactory. The model possesses the important guiding significance for actual productions.

关 键 词：卷取张力控制 RBF神经网络 逆系统 

分 类 号：TG333.24[金属学及工艺—金属压力加工]