Optimization of Rollgap Self-learning Algorithm in Tandem Hot Rolled Strip Finishing Mill

摘要：

The thickness precision is an important indicator in strip production, in which a self-learning with high precise model is necessary. In this paper, tacking new data collection and processing, looper speed compensation and more influencing factors into account, an optimized rollgap self-learning model was proposed. With the help of algorithm optimization of Newton-Raphson method, the calculation accuracy are enhanced, and make the actual thickness more approximate to the target value. The application of a 700mm tandem hot strip rolling mill shows that the model could meet the demands of on-line control with high computing precision, and the thickness accuracy are raised to a higher level.

关键词： Hot Rolled Strip Rollgap Self-learning Optimization Algorithm Newton-Raphson Method

作者: Peng Wen Zhang Dianhua Gong Dianyao

作者单位: The State Key Laboratory of Rolling and Automation, Northeastern University, Liaoning, 110819

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 3964-3967

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）