• DocumentCode
    1349345
  • Title

    Development of an optimal crown/shape level-2 control model for rolling mills with multiple control devices

  • Author

    Guo, Remn-Min

  • Author_Institution
    ARMCO Res. & Technol., Middletown, OH., USA
  • Volume
    6
  • Issue
    2
  • fYear
    1998
  • fDate
    3/1/1998 12:00:00 AM
  • Firstpage
    172
  • Lastpage
    179
  • Abstract
    Three development stages of an online crown/shape control model are discussed. Each stage bears specific consideration and provides variable information for mill operations. Theoretical derivation of the first stage facilitates understanding of mill rolling behavior. Usage of the crown/shape model leads to the development of the linear crown control system. The second-stage development is to generate an offline simulation model which bridges the gap between theory and application. It is used to verify the theoretical model, to determine control gain factors, and even to examine stability of the control algorithm. The real-time process model is last when conducting mill setup calculations. It has to cope with uncertainties of measured devices, possible errors of the theoretical model, and real-world disturbance of mill operating conditions. Providing a stable, optimal, and accurate setup for the mill is its major responsibility. Statistical methods are used everywhere in these models from tuning to optimizing processes. This optimal linear crown/shape control system has been successfully applied to a production hot strip mill since 1992. The article describes development and application of this rolling model
  • Keywords
    adaptive control; learning systems; metallurgical industries; optimal control; process control; rolling mills; shape control; statistical analysis; control gain factors; linear crown control system; mill operations; offline simulation model; optimal crown/shape level-2 control model; real-time process model; rolling behavior; rolling mills; statistical methods; Bridges; Control system synthesis; Measurement uncertainty; Milling machines; Optimal control; Optimization methods; Production systems; Shape control; Stability; Statistical analysis;
  • fLanguage
    English
  • Journal_Title
    Control Systems Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6536
  • Type

    jour

  • DOI
    10.1109/87.664184
  • Filename
    664184