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  • 标题:Explicit Model Predictive Controller Design for Thickness and Tension Control in a Cold Rolling Mill
  • 本地全文:下载
  • 作者:Tomoyoshi Ogasahara ; Morten Hovd ; Kazuya Asano
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:20
  • 页码:126-131
  • DOI:10.1016/j.ifacol.2016.10.108
  • 语种:English
  • 出版社:Elsevier
  • 摘要:This paper addresses modeling of a cold rolling mill and controller design based on explicit model predictive control(explicit MPC). The control objectives are to track the exit thickness to the reference with high accuracy with minimized strip tension deviation. In the simulation, good control is obtained when the disturbance entering the system is small enough. However, the thickness shows the offset from the reference in case of acceleration, because the approximation error of the linearized model increases and it is different from the model in the design of the controller. In order to compensate for the control offset, an additional integral logic using the estimation error of exit thickness is proposed. The validity of this approach was verified by simulation and offset free control was achieved.
  • 关键词:process controlprocess modelspredictive controloptimal controlmulti-input/multi-output systemsteel industry
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