Multi objective optimization in the level controller project in a pilot plant
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/4794 |
Resumo: | Controlling the process variables at the desired point represents from economic gain, quality in the final product and control of industrial safety. The optimization aims to search for the best solution, so that this occurs, algorithms such as Firefly Colony and Differential Evolution are used, which minimize the relative error of the controlled variable output signal. In order to compare the differential evolution algorithms and the bio-inspired: firefly colony and the classic Ziegler-Nichols method, the PI control and PID control project applied to a pilot plant was carried out, considering two final elements control systems (valve and pump) for level control, establishing the minimum effort of the manipulated variable as a performance criterion. The comparison of the results obtained between the designed controllers, using the three methods for the two elements under study, demonstrated that the optimization algorithms showed an excellent control of the process, without any overshoot (maximum deviation from the value of the controlled variable, with the setpoint value). The results obtained demonstrated that both optimization algorithms are good methods for the design of controllers when worked with the minimum effort of the manipulated variable. |
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Multi objective optimization in the level controller project in a pilot plantOptimización multiobjetivo en el proyecto de controlador de nivel en una planta pilotoOtimização multiobjetivo no projeto de controlador de nível em planta pilotoAlgoritmo bio-inspiradoControle feedbackEvolução diferencialOtimização.Algoritmo bioinspiradoControl de retroalimentaciónEvolución diferencialOptimización.Bio-inspired algorithmFeedback controlDifferential evolutionOptimization.Controlling the process variables at the desired point represents from economic gain, quality in the final product and control of industrial safety. The optimization aims to search for the best solution, so that this occurs, algorithms such as Firefly Colony and Differential Evolution are used, which minimize the relative error of the controlled variable output signal. In order to compare the differential evolution algorithms and the bio-inspired: firefly colony and the classic Ziegler-Nichols method, the PI control and PID control project applied to a pilot plant was carried out, considering two final elements control systems (valve and pump) for level control, establishing the minimum effort of the manipulated variable as a performance criterion. The comparison of the results obtained between the designed controllers, using the three methods for the two elements under study, demonstrated that the optimization algorithms showed an excellent control of the process, without any overshoot (maximum deviation from the value of the controlled variable, with the setpoint value). The results obtained demonstrated that both optimization algorithms are good methods for the design of controllers when worked with the minimum effort of the manipulated variable.El control de las variables del proceso en el punto deseado representa desde el beneficio económico, la calidad en el producto final y el control de la seguridad industrial. La optimización tiene como objetivo buscar la mejor solución, para que esto ocurra, se utilizan algoritmos como Firefly Colony y Diferencial Evolution, que minimizan el error relativo de la señal de salida de la variable controlada. Para comparar los algoritmos de evolución diferencial y la bioinspiración: colonia de luciérnagas y el método clásico Ziegler-Nichols, se llevó a cabo el proyecto de control PI y control PID aplicado a una planta piloto, considerando dos elementos finales sistemas de control (válvula y bomba) para control de nivel, estableciendo el mínimo esfuerzo de la variable manipulada como criterio de rendimiento. La comparación de los resultados obtenidos entre los controladores proyectados, utilizando los tres métodos para los dos elementos en estudio, demostró que los algoritmos de optimización mostraron un excelente control del proceso, sin ningún sobreimpulso (desviación máxima del valor de la variable controlada, con el valor del punto de ajuste). Los resultados obtenidos demostraron que ambos algoritmos de optimización son buenos métodos para el diseño de controladores cuando se trabaja con el mínimo esfuerzo de la variable manipulada.Controlar as variáveis de processo no ponto desejado representa desde ganho econômico, qualidade no produto final e controle da segurança industrial. A otimização tem como objetivo a busca pela melhor solução, para que isso ocorra utilizam-se algoritmos como Colônia de Vagalumes e o Evolução Diferencial, os quais minimizam o erro relativo do sinal de saída da variável controlada. Com o objetivo de comparar os algoritmos de evolução diferencial, e o bio-inspirado: colônia de vagalumes e o método clássico de Ziegler-Nichols, foi realizado o projeto de controle PI e de controle PID aplicado em uma planta piloto, considerando dois elementos finais de controle distintos (válvula e bomba) para controle de nível estabelecendo como critério de performance o mínimo esforço possível da variável manipulada. A comparação dos resultados obtidos entre os controladores projetados, utilizando os três métodos para os dois elementos em estudo, demonstrou que os algoritmos de otimização apresentaram um ótimo controle do processo, sem nenhum overshoot (desvio máximo do valor da variável controlada, com o valor do setpoint). Os resultados obtidos demostraram que ambos algoritmos de otimização são bons métodos para o projeto de controladores quando trabalhado com o mínimo esforço da variável manipulada.Research, Society and Development2020-06-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/479410.33448/rsd-v9i7.4794Research, Society and Development; Vol. 9 No. 7; e743974794Research, Society and Development; Vol. 9 Núm. 7; e743974794Research, Society and Development; v. 9 n. 7; e7439747942525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/4794/4152Copyright (c) 2020 Matheus Divino Moraes Oliveira, Rubia Carolina Morais Silva, Davi Leonardo de Souzainfo:eu-repo/semantics/openAccessOliveira, Matheus Divino MoraesSilva, Rubia Carolina MoraisSouza, Davi Leonardo de2020-08-20T18:05:03Zoai:ojs.pkp.sfu.ca:article/4794Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:28:31.243197Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Multi objective optimization in the level controller project in a pilot plant Optimización multiobjetivo en el proyecto de controlador de nivel en una planta piloto Otimização multiobjetivo no projeto de controlador de nível em planta piloto |
title |
Multi objective optimization in the level controller project in a pilot plant |
spellingShingle |
Multi objective optimization in the level controller project in a pilot plant Oliveira, Matheus Divino Moraes Algoritmo bio-inspirado Controle feedback Evolução diferencial Otimização. Algoritmo bioinspirado Control de retroalimentación Evolución diferencial Optimización. Bio-inspired algorithm Feedback control Differential evolution Optimization. |
title_short |
Multi objective optimization in the level controller project in a pilot plant |
title_full |
Multi objective optimization in the level controller project in a pilot plant |
title_fullStr |
Multi objective optimization in the level controller project in a pilot plant |
title_full_unstemmed |
Multi objective optimization in the level controller project in a pilot plant |
title_sort |
Multi objective optimization in the level controller project in a pilot plant |
author |
Oliveira, Matheus Divino Moraes |
author_facet |
Oliveira, Matheus Divino Moraes Silva, Rubia Carolina Morais Souza, Davi Leonardo de |
author_role |
author |
author2 |
Silva, Rubia Carolina Morais Souza, Davi Leonardo de |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Oliveira, Matheus Divino Moraes Silva, Rubia Carolina Morais Souza, Davi Leonardo de |
dc.subject.por.fl_str_mv |
Algoritmo bio-inspirado Controle feedback Evolução diferencial Otimização. Algoritmo bioinspirado Control de retroalimentación Evolución diferencial Optimización. Bio-inspired algorithm Feedback control Differential evolution Optimization. |
topic |
Algoritmo bio-inspirado Controle feedback Evolução diferencial Otimização. Algoritmo bioinspirado Control de retroalimentación Evolución diferencial Optimización. Bio-inspired algorithm Feedback control Differential evolution Optimization. |
description |
Controlling the process variables at the desired point represents from economic gain, quality in the final product and control of industrial safety. The optimization aims to search for the best solution, so that this occurs, algorithms such as Firefly Colony and Differential Evolution are used, which minimize the relative error of the controlled variable output signal. In order to compare the differential evolution algorithms and the bio-inspired: firefly colony and the classic Ziegler-Nichols method, the PI control and PID control project applied to a pilot plant was carried out, considering two final elements control systems (valve and pump) for level control, establishing the minimum effort of the manipulated variable as a performance criterion. The comparison of the results obtained between the designed controllers, using the three methods for the two elements under study, demonstrated that the optimization algorithms showed an excellent control of the process, without any overshoot (maximum deviation from the value of the controlled variable, with the setpoint value). The results obtained demonstrated that both optimization algorithms are good methods for the design of controllers when worked with the minimum effort of the manipulated variable. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-06-08 |
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 |
https://rsdjournal.org/index.php/rsd/article/view/4794 10.33448/rsd-v9i7.4794 |
url |
https://rsdjournal.org/index.php/rsd/article/view/4794 |
identifier_str_mv |
10.33448/rsd-v9i7.4794 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/4794/4152 |
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 |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 9 No. 7; e743974794 Research, Society and Development; Vol. 9 Núm. 7; e743974794 Research, Society and Development; v. 9 n. 7; e743974794 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052650745757696 |