Sequential control performance diagnosis of steel processes

Research output: Contribution to conferenceProceeding

1 Citation (Scopus)


A sequential method for Control Performance Diagnosis using a classication tree to predict possible root-causes of poor performance is presented. The classication tree methodology is used to combine process pre-assessment (nonlinearities detection, delays estimation and controller assessment), Control Performance Assessment (CPA) and ANalysis Of VAriance (ANOVA) into an integrated framework. A initial process data set is analysed and the results are used as decision thresholds for the classication tree. The methodology is capable to identify root-causes such as:poor tuning, inadequate control structure, nonlinearities, process mismatch and disturbance changes. The proposed methodology is applied to individual loops of a tandem cold rolling mill.
Original languageEnglish
Pages2830 – 2835
Number of pages6
Publication statusPublished - 24 Aug 2014
EventIFAC World Congress 2014 - Cape Town, South Africa
Duration: 24 Aug 201429 Aug 2014


ConferenceIFAC World Congress 2014
CountrySouth Africa
CityCape Town


  • closed loop identification
  • fault detection
  • fault diagnosis
  • tuning
  • filtering

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    Research Output

    • 1 Citations
    • 1 Paper

    PID based control performance assessment for rolling mills: a multiscale PCA approach

    Recalde, L. F., Katebi, R. & Tauro, H., 14 Nov 2013, p. 1075-1080. 6 p.

    Research output: Contribution to conferencePaper

  • 6 Citations (Scopus)

    Cite this

    Recalde Camacho, L., Katebi, R., & Yue, H. (2014). Sequential control performance diagnosis of steel processes. 2830 – 2835. IFAC World Congress 2014, Cape Town, South Africa.