Gray-box modeling for prediction and control of molten steel temperature in tundish

Iftikhar Ahmad, Manabu Kano, Shinji Hasebe, Hiroshi Kitada, Noboru Murata

    Research output: Contribution to journalArticle

    17 Citations (Scopus)

    Abstract

    To realize stable production in the steel industry, it is important to control molten steel temperature in a continuous casting process. The present work aims to provide a general framework of gray-box modeling and to develop a gray-box model that predicts and controls molten steel temperature in a tundish (TD temp) with high accuracy. Since the adopted first-principle model (physical model) cannot accurately describe uncertainties such as degradation of ladles, their overall heat transfer coefficient, which is a parameter in the first-principle model, is optimized for each past batch separately, then the parameter is modeled as a function of process variables through a statistical modeling method, random forests. Such a model is termed as a serial gray-box model. Prediction errors of the first-principle model or the serial gray-box model can be compensated by using another statistical model; this approach derives a parallel gray-box model or a combined gray-box model. In addition, the developed gray-box models are used to determine the optimal molten steel temperature in the Ruhrstahl-Heraeus degassing process from the target TD temp, since the continuous casting process has no manipulated variable to directly control TD temp. The proposed modeling and control strategy is validated through its application to real operation data at a steel work. The results show that the combined gray-box model achieves the best performance in prediction and control of TD temp and satisfies the requirement for its industrial application.

    Original languageEnglish
    Pages (from-to)375-382
    Number of pages8
    JournalJournal of Process Control
    Volume24
    Issue number4
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    Molten materials
    Steel
    Prediction
    Modeling
    Temperature
    First-principles
    Model
    Continuous Casting
    Continuous casting
    Ladles
    Random Forest
    Heat Transfer Coefficient
    Statistical Modeling
    Prediction Error
    Iron and steel industry
    Degassing
    Industrial Application
    Physical Model
    Modeling Method
    Statistical method

    Keywords

    • Gray-box modeling
    • Model-based control
    • Soft-sensor
    • Steel making process
    • Virtual sensing

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Industrial and Manufacturing Engineering
    • Modelling and Simulation
    • Computer Science Applications

    Cite this

    Gray-box modeling for prediction and control of molten steel temperature in tundish. / Ahmad, Iftikhar; Kano, Manabu; Hasebe, Shinji; Kitada, Hiroshi; Murata, Noboru.

    In: Journal of Process Control, Vol. 24, No. 4, 2014, p. 375-382.

    Research output: Contribution to journalArticle

    Ahmad, Iftikhar ; Kano, Manabu ; Hasebe, Shinji ; Kitada, Hiroshi ; Murata, Noboru. / Gray-box modeling for prediction and control of molten steel temperature in tundish. In: Journal of Process Control. 2014 ; Vol. 24, No. 4. pp. 375-382.
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