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Deep learning based modeling for the lateral movement of a strip in hot finishing mill SCOPUS

Title
Deep learning based modeling for the lateral movement of a strip in hot finishing mill
Authors
Kwon, W.Baek, J.Han, S.Won, S.
Date Issued
2017-01
Publisher
IEEE Computer Society
Abstract
In this paper, the problem of system identification for the lateral motion of a strip in hot finishing mill is investigated. The movement is affected by various asymmetric factors with respect to rolling force. Not only that, the tension between rolling mills determines the direction of strip's moving. Consequently, the movement of a strip is complex dynamics with rolling condition, tension and other phenomena. To identify a neural network type system model in the existence of both uncertain parameters and nonlinear signals, deep learning based modelling is employed. ? 2016 Institute of Control, Robotics and Systems - ICROS.
URI
https://oasis.postech.ac.kr/handle/2014.oak/96255
DOI
10.1109/ICCAS.2016.7832464
ISSN
1598-7833
Article Type
Article
Citation
International Conference on Control, Automation and Systems, page. 1189 - 1191, 2017-01
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