• DocumentCode
    700694
  • Title

    Dynamic system calibration by system identification methods

  • Author

    Ergon, R. ; Di Ruscio, D.

  • Author_Institution
    Telemark Inst. of Technol., Porsgrunn, Norway
  • fYear
    1997
  • fDate
    1-7 July 1997
  • Firstpage
    1556
  • Lastpage
    1561
  • Abstract
    Primary output variables from industrial processes can be estimated from known input variables and secondary process measurements. As a basis for this, the dynamic predictor has to be identified from data collected during a calibration experiment. In this paper, the theoretical basis for this is investigated, and a systematic experimental method is proposed.
  • Keywords
    calibration; identification; predictive control; process control; calibration experiment; dynamic predictor; dynamic system calibration; industrial processes; known input variables; primary output variables; secondary process measurements; system identification methods; Calibration; Estimation; Kalman filters; Mathematical model; Noise; Noise measurement; Predictive models; Estimation; multivariate calibration; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 1997 European
  • Conference_Location
    Brussels
  • Print_ISBN
    978-3-9524269-0-6
  • Type

    conf

  • Filename
    7082324