| RBF神经网络的板形预测控制 |
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| 引用本文： | 张秀玲,陈丽杰,逄宗朋,朱春颖,贾春玉.RBF神经网络的板形预测控制[J].智能系统学报,2010,5(1):70-73. |
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| 作者姓名： | 张秀玲 陈丽杰 逄宗朋 朱春颖 贾春玉 |
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| 作者单位： | 燕山大学,电气工程学院,河北,秦皇岛,066004;燕山大学,工业计算机控制工程河北省重点实验室,河北,秦皇岛,066004 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 由于板带轧制的环境十分复杂,如温度的变化是无法避免的干扰,以及HC轧机液压弯辊系统的非线性和不确定性,使得按传统理论建立的模型和控制方法都难以达到理想的效果.针对这一问题,提出了一种基于径向基函数(RBF)神经网络的模型预测控制方案应用于带材控制中,以提高带材的成材率,充分发挥液压弯辊力对板形的调整作用,改善轧机系统的动态特性.仿真结果表明了该控制系统的性能良好,有较强的抗干扰能力和较好的鲁棒性和快速性.
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| 关 键 词： | 板形控制 HC轧机 液压弯辊控制 RBF神经网络 预测控制 |
A predictive system for process control of flatness in rolling mills using a radial basis function network |
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| ZHANG Xiu-ling,CHEN Li-jie,PANG Zong-peng,ZHU Chun-ying,JIA Chun-yu.A predictive system for process control of flatness in rolling mills using a radial basis function network[J].CAAL Transactions on Intelligent Systems,2010,5(1):70-73. |
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| Authors: | ZHANG Xiu-ling CHEN Li-jie PANG Zong-peng ZHU Chun-ying JIA Chun-yu |
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| Affiliation: | ZHANG Xiu-ling1,2,CHEN Li-jie1,PANG Zong-peng1,ZHU Chun-ying1,JIA Chun-yu1,2(1.College of Electrical Engineering,Yanshan University,Qinhuangdao 066004,China,2.Key Lab of Industrial Computer Control Engineering of Hebei Province,China) |
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| Abstract: | When plate and strip rolling is done in very complex environments,such as high crown (HC) rolling mills,there are many factors that make system control difficult.Factors affecting the flatness of steel sheets include temperature changes as well as non-linearities that lead to uncertainty about results from bending roller forces.A novel predictive control program was proposed,one employing a radial basis function (RBF) neural network.It ensures flatness by controlling the bending forces of rollers.Simulation... |
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| Keywords: | shape control HC-mill hydraulic control of bending rollers RBF neural network predictive control |
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