Inferential Control of Distillation Composition Using Partial Least Squares Regression

In order to control product compositions in a multicomponent distillation column, the composition estimated from measured tray temperatures is used. In this paper, inferential models of product compositions are constructed using Partial Least Squares regression, on the basis of steady-state and time...

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Bibliographic Details
Published inKAGAKU KOGAKU RONBUNSHU Vol. 24; no. 3; pp. 425 - 430
Main Authors KANO, MANABU, MIYAZAKI, KOICHI, HASEBE, SHINJI, HASHIMOTO, IORI
Format Journal Article
LanguageJapanese
Published Tokyo The Society of Chemical Engineers, Japan 1998
Kagaku Kōgaku Kyōkai
Subjects
cascade control
distillation column
inferential control
inferential model
partial least squares
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ISSN0386-216X
1349-9203
DOI10.1252/kakoronbunshu.24.425

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Summary:In order to control product compositions in a multicomponent distillation column, the composition estimated from measured tray temperatures is used. In this paper, inferential models of product compositions are constructed using Partial Least Squares regression, on the basis of steady-state and time series temperature measurements. The accuracy of the estimation is greatly improved by using a dynamic model. It is also found that the use of past temperature measurements is effective for improv-ing the performance of the inferential model. From the detailed dynamic simulation results, it is found that the cascade control system using the proposed inferential model works very well.
ISSN:0386-216X
1349-9203
DOI:10.1252/kakoronbunshu.24.425