Multivariable Tracking Control of a Bioethanol Process under Uncertainties

Bioethanol is one of the most studied alternative fuels nowadays. Due to its production process complexity and the low quality of the mathematical models that describe it, a reliable controller is needed to maximize the fuel production and minimize its environmental impact, even in the presence of u...

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Main Authors: M. Cecilia Fernández, M. Nadia Pantano, Emanuel Serrano, Gustavo Scaglia
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/8263690
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spelling doaj-3dc03d1d2c4d4623853fee638c8989f02020-11-25T02:36:42ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/82636908263690Multivariable Tracking Control of a Bioethanol Process under UncertaintiesM. Cecilia Fernández0M. Nadia Pantano1Emanuel Serrano2Gustavo Scaglia3Instituto de Ingeniería Química, Universidad Nacional de San Juan (UNSJ), CONICET, Av. Lib. San Martín Oeste 1109, San Juan J5400ARL, ArgentinaInstituto de Ingeniería Química, Universidad Nacional de San Juan (UNSJ), CONICET, Av. Lib. San Martín Oeste 1109, San Juan J5400ARL, ArgentinaInstituto de Ingeniería Química, Universidad Nacional de San Juan (UNSJ), CONICET, Av. Lib. San Martín Oeste 1109, San Juan J5400ARL, ArgentinaInstituto de Ingeniería Química, Universidad Nacional de San Juan (UNSJ), CONICET, Av. Lib. San Martín Oeste 1109, San Juan J5400ARL, ArgentinaBioethanol is one of the most studied alternative fuels nowadays. Due to its production process complexity and the low quality of the mathematical models that describe it, a reliable controller is needed to maximize the fuel production and minimize its environmental impact, even in the presence of uncertainty. Here, a controller for tracking optimal profiles considering model errors and external perturbations is proposed. This work is an improvement of a previously presented technique. To reduce the earlier mentioned uncertainties’ effect during the fermentation, some tracking error integrators are added in the control action calculation. This simple modification ensures the tracking error convergence to zero, even in the presence of uncertainties (demonstration available). Different tests are carried out and a performance comparison with the original controller is shown to highlight improvements in the tracking error of up to 98% when integrators are incorporated. Furthermore, a classical PI controller is contrasted with the proposed techniques.http://dx.doi.org/10.1155/2020/8263690
collection DOAJ
language English
format Article
sources DOAJ
author M. Cecilia Fernández
M. Nadia Pantano
Emanuel Serrano
Gustavo Scaglia
spellingShingle M. Cecilia Fernández
M. Nadia Pantano
Emanuel Serrano
Gustavo Scaglia
Multivariable Tracking Control of a Bioethanol Process under Uncertainties
Mathematical Problems in Engineering
author_facet M. Cecilia Fernández
M. Nadia Pantano
Emanuel Serrano
Gustavo Scaglia
author_sort M. Cecilia Fernández
title Multivariable Tracking Control of a Bioethanol Process under Uncertainties
title_short Multivariable Tracking Control of a Bioethanol Process under Uncertainties
title_full Multivariable Tracking Control of a Bioethanol Process under Uncertainties
title_fullStr Multivariable Tracking Control of a Bioethanol Process under Uncertainties
title_full_unstemmed Multivariable Tracking Control of a Bioethanol Process under Uncertainties
title_sort multivariable tracking control of a bioethanol process under uncertainties
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description Bioethanol is one of the most studied alternative fuels nowadays. Due to its production process complexity and the low quality of the mathematical models that describe it, a reliable controller is needed to maximize the fuel production and minimize its environmental impact, even in the presence of uncertainty. Here, a controller for tracking optimal profiles considering model errors and external perturbations is proposed. This work is an improvement of a previously presented technique. To reduce the earlier mentioned uncertainties’ effect during the fermentation, some tracking error integrators are added in the control action calculation. This simple modification ensures the tracking error convergence to zero, even in the presence of uncertainties (demonstration available). Different tests are carried out and a performance comparison with the original controller is shown to highlight improvements in the tracking error of up to 98% when integrators are incorporated. Furthermore, a classical PI controller is contrasted with the proposed techniques.
url http://dx.doi.org/10.1155/2020/8263690
work_keys_str_mv AT mceciliafernandez multivariabletrackingcontrolofabioethanolprocessunderuncertainties
AT mnadiapantano multivariabletrackingcontrolofabioethanolprocessunderuncertainties
AT emanuelserrano multivariabletrackingcontrolofabioethanolprocessunderuncertainties
AT gustavoscaglia multivariabletrackingcontrolofabioethanolprocessunderuncertainties
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