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  • 标题:Optimal Parameter Identification for a Hydrodynamic Roll Gap Model in Hot Strip Rolling ⁎
  • 本地全文:下载
  • 作者:Martin Müller ; Andreas Steinboeck ; Katharina Prinz
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:21
  • 页码:195-200
  • DOI:10.1016/j.ifacol.2018.09.417
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWhen using modern model-based control concepts in a hot strip rolling mill, an accurate prediction of the roll force is crucial for the achieved control accuracy in terms of the strip thickness. Hence, the influence of various process parameters, e.g., lubrication, on the roll force is of central interest. Commonly used roll gap models are based on the slab method and are often not capable of describing these influences. The hydrodynamic roll gap model, however, can capture the influence of varying friction conditions between the strip and the work rolls. Varying friction conditions can be caused, for instance, by lubrication. This paper presents a combination of the hydrodynamic roll gap model with tailored material models for a more accurate prediction of the roll force in a tandem rolling mill. To parametrize the model, an optimization-based identification algorithm is proposed for unknown friction coefficients and material parameters. The identification algorithm is used on measurement data from an industrial hot strip rolling mill. A comparison with a commonly used roll gap model shows that the parametrized hydrodynamic roll gap model predicts the roll force with significantly higher accuracy.
  • 关键词:KeywordsHot strip rollingHydrodynamic roll gap modelOptimal parameter identificationLubricationNonlinear least-squares identificationSteel industry
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