摘要
通过把轧制力方程和厚度控制方程在小范围内线性化、离散化,用递推最小二乘法辨识出系统的状态空间模型.给出了基于Kalman滤波法的最优信息融合算法,并针对热连轧这个复杂的多变量系统设计了异步信息融合估计算法.将模型用于热连轧机带钢厚度预测中,同时也预测带钢塑性系数Q.最后把实时预测出的带钢出口厚度和带钢塑性系数应用于带钢热连轧厚度控制系统,提高了带钢厚度质量.
A state-space model of the control system in hot continuous rolling was proposed by using a recursive least squares algorithm by linearizing and discretizing the rolling force and thickness control equations. After an optimal information fusion algorithm based on Kalman filtering was presented, an asynchronous information fusion estimation algorithm was built for the complex multi-variable system of hot continuous rolling. This model was applied into the prediction of strip thickness and plasticity coefficient Q in the hot continuous rolling process. At last, the real-time forecast results of the coming strip thickness and plasticity coefficient of strips were synthetically utilized in the thickness control system of hot continuous rolling to improve the quality of final coming strip thickness.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
2011年第3期358-362,共5页
Journal of University of Science and Technology Beijing
基金
中央高校基本科研业务费专项基金资助项目(No.FRF--AS--09--006B)
关键词
热轧
带钢
厚度控制
最小二乘逼近
信息融合
hot rolling
strips
thickness control
least squares approximations
information fusion
