Artificial neural networks to control chlorine dosing in a water treatment plant

Detalhes bibliográficos
Autor(a) principal: Librantz, André Felipe
Data de Publicação: 2018
Outros Autores: Santos, Fábio Cosme Rodrigues dos, Dias, Cleber Gustavo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta scientiarum. Technology (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37275
Resumo: Artificial neural networks in the multivariable control of chlorine dosing in the post-chlorination stage in a water treatment plant in the Greater São Paulo, Brazil, are analyzed. The plant has constant fluctuations in chlorine demand caused by natural influences related to raw water from surface source. Modeling and computer simulation were implemented in MATLAB/Simulink® environment, according to the physical and operational characteristics of the water treatment plant. Moreover, a Proportional-Integral (PI) controller was incorporated to provide better stability. Simulation results showed improved stability of free residual chlorine when compared to method currently employed, i.e. Proportional-Integral-Derivative (PID) controller that would reduce chlorine consumption in water treatment process. 
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spelling Artificial neural networks to control chlorine dosing in a water treatment plantcomputational intelligenceprocess optimizationset-point controlwater treatment plant.Engenharia ElétricaArtificial neural networks in the multivariable control of chlorine dosing in the post-chlorination stage in a water treatment plant in the Greater São Paulo, Brazil, are analyzed. The plant has constant fluctuations in chlorine demand caused by natural influences related to raw water from surface source. Modeling and computer simulation were implemented in MATLAB/Simulink® environment, according to the physical and operational characteristics of the water treatment plant. Moreover, a Proportional-Integral (PI) controller was incorporated to provide better stability. Simulation results showed improved stability of free residual chlorine when compared to method currently employed, i.e. Proportional-Integral-Derivative (PID) controller that would reduce chlorine consumption in water treatment process. Universidade Estadual De Maringá2018-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3727510.4025/actascitechnol.v40i1.37275Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e37275Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e372751806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37275/pdfCopyright (c) 2018 Acta Scientiarum. Technologyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessLibrantz, André FelipeSantos, Fábio Cosme Rodrigues dosDias, Cleber Gustavo2019-07-17T11:53:49Zoai:periodicos.uem.br/ojs:article/37275Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2019-07-17T11:53:49Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Artificial neural networks to control chlorine dosing in a water treatment plant
title Artificial neural networks to control chlorine dosing in a water treatment plant
spellingShingle Artificial neural networks to control chlorine dosing in a water treatment plant
Librantz, André Felipe
computational intelligence
process optimization
set-point control
water treatment plant.
Engenharia Elétrica
title_short Artificial neural networks to control chlorine dosing in a water treatment plant
title_full Artificial neural networks to control chlorine dosing in a water treatment plant
title_fullStr Artificial neural networks to control chlorine dosing in a water treatment plant
title_full_unstemmed Artificial neural networks to control chlorine dosing in a water treatment plant
title_sort Artificial neural networks to control chlorine dosing in a water treatment plant
author Librantz, André Felipe
author_facet Librantz, André Felipe
Santos, Fábio Cosme Rodrigues dos
Dias, Cleber Gustavo
author_role author
author2 Santos, Fábio Cosme Rodrigues dos
Dias, Cleber Gustavo
author2_role author
author
dc.contributor.author.fl_str_mv Librantz, André Felipe
Santos, Fábio Cosme Rodrigues dos
Dias, Cleber Gustavo
dc.subject.por.fl_str_mv computational intelligence
process optimization
set-point control
water treatment plant.
Engenharia Elétrica
topic computational intelligence
process optimization
set-point control
water treatment plant.
Engenharia Elétrica
description Artificial neural networks in the multivariable control of chlorine dosing in the post-chlorination stage in a water treatment plant in the Greater São Paulo, Brazil, are analyzed. The plant has constant fluctuations in chlorine demand caused by natural influences related to raw water from surface source. Modeling and computer simulation were implemented in MATLAB/Simulink® environment, according to the physical and operational characteristics of the water treatment plant. Moreover, a Proportional-Integral (PI) controller was incorporated to provide better stability. Simulation results showed improved stability of free residual chlorine when compared to method currently employed, i.e. Proportional-Integral-Derivative (PID) controller that would reduce chlorine consumption in water treatment process. 
publishDate 2018
dc.date.none.fl_str_mv 2018-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37275
10.4025/actascitechnol.v40i1.37275
url http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37275
identifier_str_mv 10.4025/actascitechnol.v40i1.37275
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37275/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2018 Acta Scientiarum. Technology
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2018 Acta Scientiarum. Technology
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual De Maringá
publisher.none.fl_str_mv Universidade Estadual De Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e37275
Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e37275
1806-2563
1807-8664
reponame:Acta scientiarum. Technology (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta scientiarum. Technology (Online)
collection Acta scientiarum. Technology (Online)
repository.name.fl_str_mv Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv ||actatech@uem.br
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