鱼群优化下的BP网络在冷轧控制中的应用  

The application of the fish to optimize the BP network in cold rolling

作　　者：李莹[1] 王洪瑞[1] 张峻林[1] 魏立新[1] 

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

出　　处：《电子技术应用》2013年第5期125-127,131,共4页Application of Electronic Technique

基　　金：国家自然科学基金项目(U1260203);河北省自然科学基金项目(F2010001320)

摘　　要：在轧机液压AGC系统及其运行机理的基础上,建立了电液位置控制系统数学模型。通过FB Generater、C语言等对优化后的网络进行编写封装,得到了基于改进人工鱼群算法优化的神经网络智能控制器,创建了基于神经网络智能算法的CFC(连续功能图)块,并在西门子FM458平台下对电液系统模型进行控制实验。实验结果表明,人工鱼群算法优化后的神经网络控制器能够准确、快捷的达到控制要求,此方法应用于冷轧AGC控制行之有效。First of all, in the rolling mill hydraulic AGC system and its running mechanism was established on the basis of electric fluid position control system mathematical model. Using the FB Generateror C language etc, the writing and packaging of the optimized network was done, andohtained the neural network intelligent controller based on improved artificial fish algorithm. Created based on neural network intelligent algorithm CFC （continuous function chart） block and in Siemens FM458 platform on the electric liquid control system model experiment. Artificial fish algorithm optimized neural network controller can accurate and fast to control requirements, the method applied in cold rolling mill AGC control effective.

关 键 词：冷轧AGC 神经网络 人工鱼群算法 智能控制器 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]