首页 | 本学科首页   官方微博 | 高级检索  
     

基于BP网络逆模型的轧辊偏心自适应逆控制
引用本文:王亚静,刘福才,张艳欣,窦春霞,吴士昌.基于BP网络逆模型的轧辊偏心自适应逆控制[J].化工自动化及仪表,2010,37(6):9-12.
作者姓名:王亚静  刘福才  张艳欣  窦春霞  吴士昌
作者单位:燕山大学西校区电院工业计算机控制工程河北省重点实验室,河北,秦皇岛,066004
基金项目:国家自然科学基金资助项目,燕山大学博士基金资助项目,河北省自然科学基金资助项目 
摘    要:针对冷轧带钢生产中的轧辊偏心控制问题,将神经网络与自适应逆控制相结合,提出一种基于BP网络逆模型的自适应逆控制方法。将系统的动态特性控制和对象的噪声控制分成两个独立的过程,当动态性能达到最优时,对象扰动的影响也减到最小。将该方法应用到350 mm四辊可逆液压轧机上,仿真结果表明,系统具有良好的动态和稳态特性。

关 键 词:轧辊偏心  神经网络逆模型  自适应逆控制  噪声消除

Adaptive Inverse Roll Eccentricity Control Based on BPNN Inverse Model
WANG Ya-jing,LIU Fu-cai,ZHANG Yan-xin,DOU Chun-xia,WU Shi-chang.Adaptive Inverse Roll Eccentricity Control Based on BPNN Inverse Model[J].Control and Instruments In Chemical Industry,2010,37(6):9-12.
Authors:WANG Ya-jing  LIU Fu-cai  ZHANG Yan-xin  DOU Chun-xia  WU Shi-chang
Affiliation:(Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University,Qinhuangdao 066004,China)
Abstract:For roll eccentricity in cold rolling mill,neural network was combined with adaptive inverse control theory and an adaptive inverse method based on BP neural network was proposed.The dynamic characteristic control and the noise elimination were distributed to two independent courses.When the dynamic characteristic achieved optimal,the object disturb played down to the least.Apply this method to 350 mm four-roller reversing hydraulic mill,simulation results show that the dynamic and steady characteristics of the system are all quite well.
Keywords:roll eccentricity  neural network inverse model  adaptive inverse control  noise elimination
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号