Modeling, Prediction, and Control of Heating Temperature for Tube Billet

被引:3
|
作者
Mao, Yachun [1 ]
Xiao, Dong [2 ]
Niu, Dapeng [2 ]
机构
[1] Northeastern Univ, Coll Resources & Civil Engn, Shenyang 110004, Peoples R China
[2] Northeastern Univ, Informat Sci & Engn Sch, Shenyang 110004, Peoples R China
基金
中国国家自然科学基金;
关键词
EXTREME LEARNING-MACHINE; REGRESSION; DESIGN; STEEL;
D O I
10.1155/2015/576813
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.
引用
收藏
页数:10
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