Indirect adaptive predictive control applied to an industrial tank level plant

Bibliographic Details
Main Author: Iván García Martínez
Publication Date: 2011
Format: Master thesis
Language: eng
Source: Biblioteca Digital de Teses e Dissertações do ITA
Download full: http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1550
Summary: Predictive control algorithms have found growing acceptance in academic and industrial applications. However, as every control methodology, it has drawbacks, which is the need for an appropriate process model to be available. Therefore, the controller may become limited in applications with nonlinear and time-varying dynamics. When the predictions are not satisfactory due to an inappropriate model, it would be convenient to have an adaptive mechanism to match the process model and the process dynamics. In this work, SISO and MIMO formulations of indirect adaptive predictive control are implemented online to control an industrial tank level plant where process and heating tanks are operated. The experiments were carried out in conditions that are typical of an industrial situation, where the plant is nonlinear, multivariable and time varying. Results from the simulations and from the online implementation showed that the predictive control algorithm is limited when its predictive model is not representative and by implementing an adaptive mechanism these limitations have been overcome. Therefore, results show that the adaptive predictive controller outperforms the predictive controller when operating the industrial tank level plant, highlighting its potential as a solution for industrial control problems.
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spelling Indirect adaptive predictive control applied to an industrial tank level plantControle preditivoControle adaptativoPlantas industriaisControladoresSistemas não-linearesSistemas dinâmicosControlePredictive control algorithms have found growing acceptance in academic and industrial applications. However, as every control methodology, it has drawbacks, which is the need for an appropriate process model to be available. Therefore, the controller may become limited in applications with nonlinear and time-varying dynamics. When the predictions are not satisfactory due to an inappropriate model, it would be convenient to have an adaptive mechanism to match the process model and the process dynamics. In this work, SISO and MIMO formulations of indirect adaptive predictive control are implemented online to control an industrial tank level plant where process and heating tanks are operated. The experiments were carried out in conditions that are typical of an industrial situation, where the plant is nonlinear, multivariable and time varying. Results from the simulations and from the online implementation showed that the predictive control algorithm is limited when its predictive model is not representative and by implementing an adaptive mechanism these limitations have been overcome. Therefore, results show that the adaptive predictive controller outperforms the predictive controller when operating the industrial tank level plant, highlighting its potential as a solution for industrial control problems.Instituto Tecnológico de AeronáuticaElder Moreira HemerlyIván García Martínez2011-06-22info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1550reponame:Biblioteca Digital de Teses e Dissertações do ITAinstname:Instituto Tecnológico de Aeronáuticainstacron:ITAenginfo:eu-repo/semantics/openAccessapplication/pdf2019-02-02T14:02:43Zoai:agregador.ibict.br.BDTD_ITA:oai:ita.br:1550http://oai.bdtd.ibict.br/requestopendoar:null2020-05-28 19:36:38.366Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáuticatrue
dc.title.none.fl_str_mv Indirect adaptive predictive control applied to an industrial tank level plant
title Indirect adaptive predictive control applied to an industrial tank level plant
spellingShingle Indirect adaptive predictive control applied to an industrial tank level plant
Iván García Martínez
Controle preditivo
Controle adaptativo
Plantas industriais
Controladores
Sistemas não-lineares
Sistemas dinâmicos
Controle
title_short Indirect adaptive predictive control applied to an industrial tank level plant
title_full Indirect adaptive predictive control applied to an industrial tank level plant
title_fullStr Indirect adaptive predictive control applied to an industrial tank level plant
title_full_unstemmed Indirect adaptive predictive control applied to an industrial tank level plant
title_sort Indirect adaptive predictive control applied to an industrial tank level plant
author Iván García Martínez
author_facet Iván García Martínez
author_role author
dc.contributor.none.fl_str_mv Elder Moreira Hemerly
dc.contributor.author.fl_str_mv Iván García Martínez
dc.subject.por.fl_str_mv Controle preditivo
Controle adaptativo
Plantas industriais
Controladores
Sistemas não-lineares
Sistemas dinâmicos
Controle
topic Controle preditivo
Controle adaptativo
Plantas industriais
Controladores
Sistemas não-lineares
Sistemas dinâmicos
Controle
dc.description.none.fl_txt_mv Predictive control algorithms have found growing acceptance in academic and industrial applications. However, as every control methodology, it has drawbacks, which is the need for an appropriate process model to be available. Therefore, the controller may become limited in applications with nonlinear and time-varying dynamics. When the predictions are not satisfactory due to an inappropriate model, it would be convenient to have an adaptive mechanism to match the process model and the process dynamics. In this work, SISO and MIMO formulations of indirect adaptive predictive control are implemented online to control an industrial tank level plant where process and heating tanks are operated. The experiments were carried out in conditions that are typical of an industrial situation, where the plant is nonlinear, multivariable and time varying. Results from the simulations and from the online implementation showed that the predictive control algorithm is limited when its predictive model is not representative and by implementing an adaptive mechanism these limitations have been overcome. Therefore, results show that the adaptive predictive controller outperforms the predictive controller when operating the industrial tank level plant, highlighting its potential as a solution for industrial control problems.
description Predictive control algorithms have found growing acceptance in academic and industrial applications. However, as every control methodology, it has drawbacks, which is the need for an appropriate process model to be available. Therefore, the controller may become limited in applications with nonlinear and time-varying dynamics. When the predictions are not satisfactory due to an inappropriate model, it would be convenient to have an adaptive mechanism to match the process model and the process dynamics. In this work, SISO and MIMO formulations of indirect adaptive predictive control are implemented online to control an industrial tank level plant where process and heating tanks are operated. The experiments were carried out in conditions that are typical of an industrial situation, where the plant is nonlinear, multivariable and time varying. Results from the simulations and from the online implementation showed that the predictive control algorithm is limited when its predictive model is not representative and by implementing an adaptive mechanism these limitations have been overcome. Therefore, results show that the adaptive predictive controller outperforms the predictive controller when operating the industrial tank level plant, highlighting its potential as a solution for industrial control problems.
publishDate 2011
dc.date.none.fl_str_mv 2011-06-22
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
status_str publishedVersion
format masterThesis
dc.identifier.uri.fl_str_mv http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1550
url http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1550
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Tecnológico de Aeronáutica
publisher.none.fl_str_mv Instituto Tecnológico de Aeronáutica
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações do ITA
instname:Instituto Tecnológico de Aeronáutica
instacron:ITA
reponame_str Biblioteca Digital de Teses e Dissertações do ITA
collection Biblioteca Digital de Teses e Dissertações do ITA
instname_str Instituto Tecnológico de Aeronáutica
instacron_str ITA
institution ITA
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáutica
repository.mail.fl_str_mv
subject_por_txtF_mv Controle preditivo
Controle adaptativo
Plantas industriais
Controladores
Sistemas não-lineares
Sistemas dinâmicos
Controle
_version_ 1706809271430152192