Inferential Control of Distillation Composition Using Partial Least Squares Regression.
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- KANO MANABU
- Department of Chemical Engineering, Kyoto University
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- MIYAZAKI KOICHI
- Department of Chemical Engineering, Kyoto University
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- HASEBE SHINJI
- Department of Chemical Engineering, Kyoto University
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- HASHIMOTO IORI
- Department of Chemical Engineering, Kyoto University
Bibliographic Information
- Other Title
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- Partial Least Squares Regressionを用いた蒸留塔製品組成の推定制御
- Partial Least Squares Regression オ モチイタ
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Abstract
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.
Journal
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- KAGAKU KOGAKU RONBUNSHU
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KAGAKU KOGAKU RONBUNSHU 24 (3), 425-430, 1998
The Society of Chemical Engineers, Japan
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Keywords
Details
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- CRID
- 1390001204508246912
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- NII Article ID
- 10002910148
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- NII Book ID
- AN00037234
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- ISSN
- 13499203
- 0386216X
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- NDL BIB ID
- 4492452
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed