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http://dx.doi.org/10.3795/KSME-A.2017.41.1.063

A Learning Model of Forward Slip Ratio Based on Model Identification in Hot Strip Finishing Mill Process  

Hwang, I Cheol (Dept. of Mechatronics Engineering, Dongeui Univ.)
Kim, Shin Il (Technical Research Laboratories, POSCO)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.41, no.1, 2017 , pp. 63-68 More about this Journal
Abstract
This paper reviews the learning model of a forward slip ratio in order to improve the mass-flow stability and strip qualities in the hot strip finishing mill process. Firstly, it is shown, from mathematical analysis, that the significant parameters of the forward slip ratio are the tension, looper angle, and roll velocity. Secondly, a discrete-time learning model of the forward slip ratio is proposed from these parameters, which is identified by an instrumental variable (IV) identification algorithm. Finally, it is shown from computer simulation that the proposed learning model is more effective than the existing learning model.
Keywords
Hot Strip Finishing Mill Process; Forward Slip Ratio; Learning Model; Model Identification; Instrumental Variable Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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