Staff View: Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column

Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column

A framework is proposed to optimize the operation of batch columns with substantial reduction of the computational power needed to carry out the optimization calculations. The proposed framework relies on the use of an artificial neural network (ANN) based process model to be employed by the optimiz...

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Main Authors:	Greaves, M.A., Mujtaba, I.M., Barolo, M., Trotta, A., Hussain, Mohd Azlan
Format:	Article
Published:	Elsevier 2003
Subjects:	TA Engineering (General). Civil engineering (General) TP Chemical technology
Online Access:	http://eprints.um.edu.my/7070/ https://doi.org/10.1205/02638760360596946
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id	my.um.eprints.7070
record_format	eprints
spelling	my.um.eprints.70702019-09-25T09:19:46Z http://eprints.um.edu.my/7070/ Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column Greaves, M.A. Mujtaba, I.M. Barolo, M. Trotta, A. Hussain, Mohd Azlan TA Engineering (General). Civil engineering (General) TP Chemical technology A framework is proposed to optimize the operation of batch columns with substantial reduction of the computational power needed to carry out the optimization calculations. The proposed framework relies on the use of an artificial neural network (ANN) based process model to be employed by the optimizer. To test the viability of the framework, the optimization of a pilot-plant middle-vessel batch column (MVBC) is considered. The maximum-product problem is formulated and solved by optimizing the column operating parameters, such as the reflux and reboil ratios and the batch time. It is shown that the ANN based model is capable of reproducing the actual plant dynamics with good accuracy, and that the proposed framework allows a large number of optimization studies to be carried out with little computational effort. Elsevier 2003 Article PeerReviewed Greaves, M.A. and Mujtaba, I.M. and Barolo, M. and Trotta, A. and Hussain, Mohd Azlan (2003) Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column. Chemical Engineering Research and Design, 81 (A3). pp. 393-401. ISSN 0263-8762 https://doi.org/10.1205/02638760360596946 doi:10.1205/02638760360596946
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	TA Engineering (General). Civil engineering (General) TP Chemical technology
spellingShingle	TA Engineering (General). Civil engineering (General) TP Chemical technology Greaves, M.A. Mujtaba, I.M. Barolo, M. Trotta, A. Hussain, Mohd Azlan Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column
description	A framework is proposed to optimize the operation of batch columns with substantial reduction of the computational power needed to carry out the optimization calculations. The proposed framework relies on the use of an artificial neural network (ANN) based process model to be employed by the optimizer. To test the viability of the framework, the optimization of a pilot-plant middle-vessel batch column (MVBC) is considered. The maximum-product problem is formulated and solved by optimizing the column operating parameters, such as the reflux and reboil ratios and the batch time. It is shown that the ANN based model is capable of reproducing the actual plant dynamics with good accuracy, and that the proposed framework allows a large number of optimization studies to be carried out with little computational effort.
format	Article
author	Greaves, M.A. Mujtaba, I.M. Barolo, M. Trotta, A. Hussain, Mohd Azlan
author_facet	Greaves, M.A. Mujtaba, I.M. Barolo, M. Trotta, A. Hussain, Mohd Azlan
author_sort	Greaves, M.A.
title	Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column
title_short	Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column
title_full	Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column
title_fullStr	Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column
title_full_unstemmed	Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column
title_sort	neural-network approach to dynamic optimization of batch distillation: application to a middle-vessel column
publisher	Elsevier
publishDate	2003
url	http://eprints.um.edu.my/7070/ https://doi.org/10.1205/02638760360596946
_version_	1646210123986632704
score	13.244745

Neural-network approach to dynamic optimization of batch distillation: Application to a middle-vessel column

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