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Structural and parametric identification of soft sensors models for process plants based on robust regression and information criteria

  • Automation in Industry
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Abstract

Approach to the solution of a problem of structural and parametrical identification of models of the soft sensors (SS) of technological plants on the basis of robust regression and information criteria is proposed. The robust regression is used for model parameter estimation, and choosing the best model structure in the sense of information criteria. SS is developed by means of the proposed approach which was tested in control systems for optimization of the process operation of gas separation section of fluid catalytic cracking unit of “OJSC Gazpromneft-Omsk Refinery.”

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Authors and Affiliations

  1. Institute of Automation and Control Processes, Far Eastern Branch, Russian Academy of Sciences, Vladivostok, Russia

    G. B. Digo, N. B. Digo & A. Yu. Torgashov

  2. “OJSC Gazpromneft-Omsk Refinery”, Omsk, Russia

    A. V. Kozlov

  3. Far Eastern Federal University, Vladivostok, Russia

    S. A. Samotylova

Authors
  1. G. B. Digo
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  2. N. B. Digo
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  3. A. V. Kozlov
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  4. S. A. Samotylova
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  5. A. Yu. Torgashov
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Corresponding author

Correspondence to A. Yu. Torgashov.

Additional information

Original Russian Text © G.B. Digo, N.B. Digo, A.V. Kozlov, S.A. Samotylova, A.Yu. Torgashov, 2015, published in Avtomatizatsiya v Promyshlennosti, 2015, No. 10, pp. 58–62.

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Digo, G.B., Digo, N.B., Kozlov, A.V. et al. Structural and parametric identification of soft sensors models for process plants based on robust regression and information criteria. Autom Remote Control 78, 724–731 (2017). https://doi.org/10.1134/S0005117917040130

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  • DOI: https://doi.org/10.1134/S0005117917040130

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