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基于神经网络的轧机液压AGC系统自适应辨识
引用本文:王益群,王海芳,高英杰,张伟.基于神经网络的轧机液压AGC系统自适应辨识[J].中国机械工程,2004,15(5):450-453.
作者姓名:王益群  王海芳  高英杰  张伟
作者单位:燕山大学机械工程学院,秦皇岛,066004
基金项目:国家自然科学基金资助项目 (60 0 740 2 2 )
摘    要:在分析液压 AGC的组成元件及其动态特性的基础上 ,利用神经网络具有逼近任何非线性函数且具有自学习和自适应的能力 ,建立基于时间序列的前馈动态模型辨识结构 ,应用扩展 BP算法对轧机液压 AGC力控制系统进行非线性预测 ,将预测结果应用最小二乘辨识方法进行线性系统的特征参数辨识 ,仿真及实测结果表明此方法行之有效 ,为轧机液压 AGC的辨识提供了新途径。

关 键 词:自适应辨识  板带轧机  液压AGC  神经网络
文章编号:1004-132Ⅹ(2004)05-0450-04
修稿时间:2002年12月25

Neural Network Based Adaptive Identification for Hydraulic AGC System in Strip Mill
Wang Yiqun Wang Haifang Gao Yingjie Zhang Wei,Yanshan University Qinhuangdao.Neural Network Based Adaptive Identification for Hydraulic AGC System in Strip Mill[J].China Mechanical Engineering,2004,15(5):450-453.
Authors:Wang Yiqun Wang Haifang Gao Yingjie Zhang Wei  Yanshan University Qinhuangdao
Affiliation:Wang Yiqun Wang Haifang Gao Yingjie Zhang Wei Yanshan University Qinhuangdao,066004
Abstract:Based on studying the components of hydraulic AGC system, and analyzing the dynamic peculiarities of the components, a new adaptive identification method was proposed for a nonliner hydraulic AGC press system in stripe mill, in which a feedforward and dynamic neural network structure was built.Using enlarged backpropagation algorithm,the nonlinear performance of force control system of the hydraulic AGC system can be predicted.Based on the predicted results the characteristic parameters of linear system were identified by least square method. Finally, the applicability of the adaptive identification method was illustrated and verified by simulation results.
Keywords:adaptive identification  stripe mill  hydraulic AGC  neural network  
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