Advanced process control of fatty acid distillation column using artificial neural networks

This thesis discusses the application of neural networks in a fatty acids distillation process control. The objective was to fulfill product purity specifications under varying feed compositions and large process disturbances. The research activities were divided into four main parts. First, a fatty...

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Main Author:	Wong, Teck Siang
Format:	Thesis
Language:	English
Published:	2003
Subjects:	TP Chemical technology
Online Access:	http://eprints.utm.my/id/eprint/42598/1/WongTeckSiangFKKKSA2003.pdf
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id	my-utm-ep.42598
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spelling	my-utm-ep.425982017-10-17T14:51:05Z Advanced process control of fatty acid distillation column using artificial neural networks 2003 Wong, Teck Siang TP Chemical technology This thesis discusses the application of neural networks in a fatty acids distillation process control. The objective was to fulfill product purity specifications under varying feed compositions and large process disturbances. The research activities were divided into four main parts. First, a fatty acids distillation process was simulated using HYSYS.Plant1M software. The simulation model was able to closely match the actual process plant data. The model was therefore considered as a reasonable representation of the actual process. Second, a neural network estimator was formulated for a product composition. Here, secondary variables as well as their past values were carefully selected to formulate an accurate and parsimonious model.Third, the inferential model was implemented as an integral part of an inferential control scheme in the distillation column. Simulation results obtained affirmed the potentials of the proposed inferential strategy for composition control. Significant improvements were obtained compared to the widely used strategy of controlling a column temperature. Finally, a neural network based model predictive control scheme was investigated. The implementation on composition control of the distillation process also produced promising results. In conclusion, the works undertaken here have exposed the potentials of neural network models in solving industrial control problems, particularly for composition control in a distillation column. 2003 Thesis http://eprints.utm.my/id/eprint/42598/ http://eprints.utm.my/id/eprint/42598/1/WongTeckSiangFKKKSA2003.pdf application/pdf en public http://libraryopac.utm.my/client/en_AU/main/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:387238/one?qu=Advanced+process+control+of+fatty+acid+distillation+column+using+artificial+neural+networks masters Universiti Teknologi Malaysia, Faculty of Chemical Engineering Faculty of Chemical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TP Chemical technology
spellingShingle	TP Chemical technology Wong, Teck Siang Advanced process control of fatty acid distillation column using artificial neural networks
description	This thesis discusses the application of neural networks in a fatty acids distillation process control. The objective was to fulfill product purity specifications under varying feed compositions and large process disturbances. The research activities were divided into four main parts. First, a fatty acids distillation process was simulated using HYSYS.Plant1M software. The simulation model was able to closely match the actual process plant data. The model was therefore considered as a reasonable representation of the actual process. Second, a neural network estimator was formulated for a product composition. Here, secondary variables as well as their past values were carefully selected to formulate an accurate and parsimonious model.Third, the inferential model was implemented as an integral part of an inferential control scheme in the distillation column. Simulation results obtained affirmed the potentials of the proposed inferential strategy for composition control. Significant improvements were obtained compared to the widely used strategy of controlling a column temperature. Finally, a neural network based model predictive control scheme was investigated. The implementation on composition control of the distillation process also produced promising results. In conclusion, the works undertaken here have exposed the potentials of neural network models in solving industrial control problems, particularly for composition control in a distillation column.
format	Thesis
qualification_level	Master's degree
author	Wong, Teck Siang
author_facet	Wong, Teck Siang
author_sort	Wong, Teck Siang
title	Advanced process control of fatty acid distillation column using artificial neural networks
title_short	Advanced process control of fatty acid distillation column using artificial neural networks
title_full	Advanced process control of fatty acid distillation column using artificial neural networks
title_fullStr	Advanced process control of fatty acid distillation column using artificial neural networks
title_full_unstemmed	Advanced process control of fatty acid distillation column using artificial neural networks
title_sort	advanced process control of fatty acid distillation column using artificial neural networks
granting_institution	Universiti Teknologi Malaysia, Faculty of Chemical Engineering
granting_department	Faculty of Chemical Engineering
publishDate	2003
url	http://eprints.utm.my/id/eprint/42598/1/WongTeckSiangFKKKSA2003.pdf
_version_	1747816808582217728

Advanced process control of fatty acid distillation column using artificial neural networks

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