Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process

Detalhes bibliográficos
Autor(a) principal: Petchinathan,G.
Data de Publicação: 2014
Outros Autores: Valarmathi,K., Devaraj,D., Radhakrishnan,T. K.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Chemical Engineering
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000200019
Resumo: This paper describes the modelling and control of a pH neutralization process using a Local Linear Model Tree (LOLIMOT) and an adaptive neuro-fuzzy inference system (ANFIS). The Direct and Inverse model building using LOLIMOT and ANFIS structures is described and compared. The direct and inverse models of the pH system are identified based on experimental data for the LOLIMOT and ANFIS structures. The identified models are implemented in the experimental pH system with IMC structure using a GUI developed in the MATLAB -SIMULINK platform. The main aim is to illustrate the online modelling and control of the experimental setup. The results of real-time control of an experimental pH process using the Internal Model Control (IMC) strategy are also presented.
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spelling Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization processLOLIMOTANFISInternal Model ControlpH processThis paper describes the modelling and control of a pH neutralization process using a Local Linear Model Tree (LOLIMOT) and an adaptive neuro-fuzzy inference system (ANFIS). The Direct and Inverse model building using LOLIMOT and ANFIS structures is described and compared. The direct and inverse models of the pH system are identified based on experimental data for the LOLIMOT and ANFIS structures. The identified models are implemented in the experimental pH system with IMC structure using a GUI developed in the MATLAB -SIMULINK platform. The main aim is to illustrate the online modelling and control of the experimental setup. The results of real-time control of an experimental pH process using the Internal Model Control (IMC) strategy are also presented.Brazilian Society of Chemical Engineering2014-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000200019Brazilian Journal of Chemical Engineering v.31 n.2 2014reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/0104-6632.20140312s00002287info:eu-repo/semantics/openAccessPetchinathan,G.Valarmathi,K.Devaraj,D.Radhakrishnan,T. K.eng2014-07-07T00:00:00Zoai:scielo:S0104-66322014000200019Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2014-07-07T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false
dc.title.none.fl_str_mv Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
title Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
spellingShingle Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
Petchinathan,G.
LOLIMOT
ANFIS
Internal Model Control
pH process
title_short Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
title_full Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
title_fullStr Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
title_full_unstemmed Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
title_sort Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
author Petchinathan,G.
author_facet Petchinathan,G.
Valarmathi,K.
Devaraj,D.
Radhakrishnan,T. K.
author_role author
author2 Valarmathi,K.
Devaraj,D.
Radhakrishnan,T. K.
author2_role author
author
author
dc.contributor.author.fl_str_mv Petchinathan,G.
Valarmathi,K.
Devaraj,D.
Radhakrishnan,T. K.
dc.subject.por.fl_str_mv LOLIMOT
ANFIS
Internal Model Control
pH process
topic LOLIMOT
ANFIS
Internal Model Control
pH process
description This paper describes the modelling and control of a pH neutralization process using a Local Linear Model Tree (LOLIMOT) and an adaptive neuro-fuzzy inference system (ANFIS). The Direct and Inverse model building using LOLIMOT and ANFIS structures is described and compared. The direct and inverse models of the pH system are identified based on experimental data for the LOLIMOT and ANFIS structures. The identified models are implemented in the experimental pH system with IMC structure using a GUI developed in the MATLAB -SIMULINK platform. The main aim is to illustrate the online modelling and control of the experimental setup. The results of real-time control of an experimental pH process using the Internal Model Control (IMC) strategy are also presented.
publishDate 2014
dc.date.none.fl_str_mv 2014-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000200019
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000200019
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0104-6632.20140312s00002287
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
dc.source.none.fl_str_mv Brazilian Journal of Chemical Engineering v.31 n.2 2014
reponame:Brazilian Journal of Chemical Engineering
instname:Associação Brasileira de Engenharia Química (ABEQ)
instacron:ABEQ
instname_str Associação Brasileira de Engenharia Química (ABEQ)
instacron_str ABEQ
institution ABEQ
reponame_str Brazilian Journal of Chemical Engineering
collection Brazilian Journal of Chemical Engineering
repository.name.fl_str_mv Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)
repository.mail.fl_str_mv rgiudici@usp.br||rgiudici@usp.br
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