Multi-Output Soft Sensor with a Multivariate Filter That Predicts Errors Applied to an Industrial Reactive Distillation Process

Vladimir Klimchenko, Andrei Torgashov, Yuri A. W. Shardt and Fan Yang
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Vladimir Klimchenko: Process Control Laboratory, Institute of Automation and Control Process FEB RAS, 5 Radio Str., Vladivostok 690041, Russia
Andrei Torgashov: Process Control Laboratory, Institute of Automation and Control Process FEB RAS, 5 Radio Str., Vladivostok 690041, Russia
Yuri A. W. Shardt: Department of Automation Engineering, Technical University of Ilmenau, 99084 Ilmenau, Germany
Fan Yang: Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China

Mathematics, 2021, vol. 9, issue 16, 1-14

Abstract: The paper deals with the problem of developing a multi-output soft sensor for the industrial reactive distillation process of methyl tert-butyl ether production. Unlike the existing soft sensor approaches, this paper proposes using a soft sensor with filters to predict model errors, which are then taken into account as corrections in the final predictions of outputs. The decomposition of the problem of optimal estimation of time delays is proposed for each input of the soft sensor. Using the proposed approach to predict the concentrations of methyl sec-butyl ether, methanol, and the sum of dimers and trimers of isobutylene in the output product in a reactive distillation column was shown to improve the results by 32%, 67%, and 9.5%, respectively.

Keywords: soft sensing; multivariate filter; reactive distillation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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