Structural and parametric identification of soft sensors models for process plants based on robust regression and information criteria
- Autores: Digo G.B.1, Digo N.B.1, Kozlov A.V.2, Samotylova S.A.3, Torgashov A.Y.1
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Afiliações:
- Institute of Automation and Control Processes, Far Eastern Branch
- “OJSC Gazpromneft-Omsk Refinery”
- Far Eastern Federal University
- Edição: Volume 78, Nº 4 (2017)
- Páginas: 724-731
- Seção: Automation in Industry
- URL: https://ogarev-online.ru/0005-1179/article/view/150584
- DOI: https://doi.org/10.1134/S0005117917040130
- ID: 150584
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Resumo
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.”
Sobre autores
G. Digo
Institute of Automation and Control Processes, Far Eastern Branch
Email: torgashov@iacp.dvo.ru
Rússia, Vladivostok
N. Digo
Institute of Automation and Control Processes, Far Eastern Branch
Email: torgashov@iacp.dvo.ru
Rússia, Vladivostok
A. Kozlov
“OJSC Gazpromneft-Omsk Refinery”
Email: torgashov@iacp.dvo.ru
Rússia, Omsk
S. Samotylova
Far Eastern Federal University
Email: torgashov@iacp.dvo.ru
Rússia, Vladivostok
A. Torgashov
Institute of Automation and Control Processes, Far Eastern Branch
Autor responsável pela correspondência
Email: torgashov@iacp.dvo.ru
Rússia, Vladivostok
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