Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol
Introducción— Modelos de reactores anteriores han sido utilizados para estudiar el comportamiento dinámico de sistemas de producción de bioetanol, sin embargo, pocos han elaborado un estudio comparativo de estrategias de control que estabilicen y controlen las variables de interés. Objetivo— El obje...
- Autores:
-
Muñoz Ñungo , Oneida
Munoz, José Aldemar
Hernández Sarabia, Héctor Mauricio
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/12329
- Palabra clave:
- Alcoholic fermentation
PID control
Fuzzy control
non-linear systems; stability
fermentación alcohólica
control PID
control Fuzzy
sistemas no lineales
estabilidad
- Rights
- openAccess
- License
- INGE CUC - 2022
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| dc.title.spa.fl_str_mv |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| dc.title.translated.eng.fl_str_mv |
Dynamic analysis and comparison of control techniques in the process of obtaining bioethanol |
| title |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| spellingShingle |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol Alcoholic fermentation PID control Fuzzy control non-linear systems; stability fermentación alcohólica control PID control Fuzzy sistemas no lineales estabilidad |
| title_short |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| title_full |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| title_fullStr |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| title_full_unstemmed |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| title_sort |
Análisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanol |
| dc.creator.fl_str_mv |
Muñoz Ñungo , Oneida Munoz, José Aldemar Hernández Sarabia, Héctor Mauricio |
| dc.contributor.author.spa.fl_str_mv |
Muñoz Ñungo , Oneida Munoz, José Aldemar Hernández Sarabia, Héctor Mauricio |
| dc.subject.eng.fl_str_mv |
Alcoholic fermentation PID control Fuzzy control non-linear systems; stability |
| topic |
Alcoholic fermentation PID control Fuzzy control non-linear systems; stability fermentación alcohólica control PID control Fuzzy sistemas no lineales estabilidad |
| dc.subject.spa.fl_str_mv |
fermentación alcohólica control PID control Fuzzy sistemas no lineales estabilidad |
| description |
Introducción— Modelos de reactores anteriores han sido utilizados para estudiar el comportamiento dinámico de sistemas de producción de bioetanol, sin embargo, pocos han elaborado un estudio comparativo de estrategias de control que estabilicen y controlen las variables de interés. Objetivo— El objetivo del presente estudio es analizar la estabilidad de un sistema de fermentación para obtención de bioetanol, su comportamiento dinámico, la caracterización de puntos de equilibrio y puntos de bifurcación del modelo matemático planteado por Jarzebski en 1992 para una fermentación continua, teniendo en cuenta el rendimiento de la reacción en un biorreactor y la aplicación de técnicas de control industrial para su optimización. Metodología— Se utilizaron métodos de revisión y diseño de tipo cuantitativo y sistematizado. Resultados— Se presenta la comparación entre dos estrategias de control para controlar la producción de bioetanol, el control PID y el control Fuzzy. Se observó un mejor comportamiento dinámico cuando se utilizó el controlador Fuzzy. Conclusiones— Este trabajo muestra la importancia del análisis de estabilidad de un sistema en continuo y cómo éste puede definir las regiones de interés operativo, en este caso para la producción de etanol, mostrando que la productividad es inversamente proporcional a la tasa de dilución. Finalmente, se concluye que se tiene un mejor comportamiento dinámico del sistema cuando se utiliza un controlador Fuzzy. |
| publishDate |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2022-09-11 00:00:00 2024-04-09T20:21:39Z |
| dc.date.available.none.fl_str_mv |
2022-09-11 00:00:00 2024-04-09T20:21:39Z |
| dc.date.issued.none.fl_str_mv |
2022-09-11 |
| dc.type.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1 |
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Text |
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Journal article |
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http://purl.org/redcol/resource_type/ART |
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https://hdl.handle.net/11323/12329 |
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https://doi.org/10.17981/ingecuc.18.2.2022.03 |
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10.17981/ingecuc.18.2.2022.03 |
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2382-4700 |
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eng |
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Inge Cuc |
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A. Jarzębski, “Modelling of oscillatory behaviour in continuous ethanol fermentation,” Biotechnol. Lett., vol. 14, no. 2, pp. 137–142, Feb. 1992. https://doi.org/10.1007/BF01026241 J. Sadhukhan, E. Martinez-Hernandez, M. Amezcua-Allieri, J. Aburto & J. Honorato, “Economic and environmental impact evaluation of various biomass feedstock for bioethanol production and correlations to lignocellulosic composition,” Bioresour. Technol. Reports, vol. 7, no. 1, pp. 1–10, Sep. 2019. https://doi.org/10.1016/j.biteb.2019.100230 B. Šantek, G. Gwehenberger, M. I. Šantek, M. Narodoslawsky & P. Horvat, “Evaluation of energy demand and the sustainability of different bioethanol production processes from sugar beet,” Resour. Conserv. Recycl., vol. 54, no. 11, pp. 872–877, Sep. 2010. https://doi.org/10.1016/j.resconrec.2010.01.006 P. Iodice, G. Langella & A. Amoresano, “Ethanol in gasoline fuel blends: Effect on fuel consumption and engine out emissions of SI engines in cold operating conditions,” Appl. Therm. Eng., vol. 130, pp. 1081–1089, Feb. 2018. https://doi.org/10.1016/j.applthermaleng.2017.11.090 J. Mantilla, D. Garzon & C. Galeano, “Análisis multivariable del desempeño y las emisiones en motores de combustión interna que utilizan mezclas de gasolina y etanol,” Ing. Energética, vol. 36, no. 3, pp. 232–242, Sep. 2015. Available: https://rie.cujae.edu.cu/index.php/RIE/article/view/451 República de Colombia. Superintendencia de Industria y Comercio, Resolución No. 40785 de 8 de julio de 2013, por la cual se concede un registro. Disponible en http://visordocs.sic.gov.co/documentos/Docs029/ActosEnLinea001/R-40785-2013.PDF?72 A. Yousefi-Darani, O. Paquet-Durand & B. Hitzmann, “Application of fuzzy logic control for the dough proofing process,” Food Bioprod. Process., vol. 115, pp. 36–46, May. 2019. https://doi.org/10.1016/j.fbp.2019.02.006 I. Edeh, “Bioethanol Production: An Overview,” in F. L. Inambao, Ed., Bioethanol Technologies, LDN, UK: IntechOpen, 2020. https://doi.org/10.5772/intechopen.94895 D. Bernier-Oviedo, J. Rincón-Moreno, J. Solanilla, J. Muñoz & H. Váquiro, “Comparison of two pretreatments methods to produce second-generation bioethanol resulting from sugarcane bagasse,” Ind. Crops Prod., vol. 122, pp. 414–421, Oct. 2018. https://doi.org/10.1016/j.indcrop.2018.06.012 M. Toor, S. Kumar, S. Malyan, N. Bishnoi, T. Mathmani, K. Rajedran & A. Pugazhendhi, “An overview on bioethanol production from lignocellulosic feedstocks,” Chemosphere, vol. 242, pp. 1–10, Mar. 2020. https://doi.org/10.1016/j.chemosphere.2019.125080 D. Maurya, A. Singla & S. Negi, “An overview of key pretreatment processes for biological conversion of lignocellulosic biomass to bioethanol,” 3 Biotech, vol. 5, no. 5, pp. 597–609, Feb. 2015. https://doi.org/10.1007/s13205-015-0279-4 N. Pachauri, A. Rani & V. Singh, “Bioreactor temperature control using modified fractional order IMC-PID for ethanol production,” Chem. Eng. Res. Des., vol. 122, pp. 97–112, Jun. 2017. https://doi.org/10.1016/j.cherd.2017.03.031 A. Ciesielski, & R. Grzywacz, “Dynamic bifurcations in continuous process of bioethanol production under aerobic conditions using Saccharomyces cerevisiae,” Biochem. Eng. J., vol. 161, pp. 1–10, Sep. 2020. https://doi.org/10.1016/j.bej.2020.107609 I. Pataro, M. da Costa, & B. Joseph, “Closed-loop dynamic real-time optimization (CL-DRTO) of a bioethanol distillation process using an advanced multilayer control architecture,” Comput. Chem. Eng., vol. 143, pp. 1–10, Dec. 2020. https://doi.org/10.1016/j.compchemeng.2020.107075 E. Imamoglu & F. Sukan, “Scale-up and kinetic modeling for bioethanol production,” Bioresour. Technol., vol. 144, pp. 311–320, Sep. 2013. https://doi.org/10.1016/j.biortech.2013.06.118 S. Fan, S, Chen, X. Tang, Z. Xiao, Q. Deng, P. Yao, Z. Sun, Y. Zhang & C. Chen, “Kinetic model of continuous ethanol fermentation in closed-circulating process with pervaporation membrane bioreactor by Saccharomyces cerevisiae,” Bioresour. Technol., vol. 177, pp. 169–175, Feb. 2015. https://doi.org/10.1016/j.biortech.2014.11.076 M. Muslim, T. Sukma Yudha & B. Ibrahim, “Feedback-feedforward fuzzy logic approach for temperature control in bioethanol vacuum distiller,” Indones. J. Electr. Eng. Comput. Sci., vol. 16, no. 2, pp. 678–684, Nov. 2019. https://doi.org/10.11591/ijeecs.v16.i2.pp678-684 F. Wang & H. Lin, “Fuzzy optimization of continuous fermentations with cell recycling for ethanol production,” Ind. Eng. Chem. Res., vol. 49, no. 5, pp. 2306–2311, Jan. 2010. https://doi.org/10.1021/ie901066a J. Gomes, J. Batra, V. Chopda, P. Kathiresan & A. Rathore, “Monitoring and control of bioethanol production from lignocellulosic biomass,” in T. Bhaskar, A. Pandey, S. V. Mohan, D.-J. Lee, S. K. Khanal, eds., Waste Biorefinery: Potential and Perspectives, ch. 25, A-M-S, NL: Elsevier, 2018, pp. 727–749. https://doi.org/10.1016/B978-0-444-63992-9.00025-2 E. Petre, D. Selişteanu, & M. Roman, “Advanced nonlinear control strategies for a fermentation bioreactor used for ethanol production,” Bioresour. Technol., vol. 328, pp. 1–10, May. 2021. https://doi.org/10.1016/j.biortech.2021.124836 A. Daugulis, P. McLellan & J. Li, “Experimental investigation and modeling of oscillatory behavior in the continuous culture ofZymomonas mobilis,” Biotechnol. Bioeng., vol. 56, no. 1, pp. 99–105, Oct. 1997. https://doi.org/10.1002/(SICI)1097-0290(19971005)56:1<99::AID-BIT11>3.0.CO;2-5 M. Henson, “Dynamic modeling of microbial cell populations,” COBIOT, vol. 14, no. 5, pp. 460–467, Oct. 2003. https://doi.org/10.1016/S0958-1669(03)00104-6 F. Lei, M. Rotboll & S. Jorgensen, “A biochemically structured model for Saccharomyces cerevisiae,” J. Biotechnol., vol. 88, no. 3, pp. 205–221, Jul. 2001. https://doi.org/10.1016/S0168-1656(01)00269-3 C. Strässle, B. Sonnleitner & A. Fiechter, “A predictive model for the spontaneous synchronization of Saccharomyces cerevisiae grown in continuous culture. II. Experimental verification,” J. Biotechnol., vol. 9, no. 3, pp. 191–208, Feb. 1989. https://doi.org/10.1016/0168-1656(89)90108-9 I. Jöbses, G. Egberts, A. van Baalen & J. Roels, “Mathematical modelling of growth and substrate conversion of Zymomonas mobilis at 30 and 35°C,” Biotechnol. Bioeng., vol. 27, no. 7, pp. 984–995, Jul. 1985. https://doi.org/10.1002/bit.260270709 P. Garhyan & S. Elnashaie, “Bifurcation analysis of two continuous membrane fermentor configurations for producing ethanol,” Chem. Eng. Sci., vol. 59, no. 15, pp. 3235–3268, Aug. 2004. https://doi.org/10.1016/j.ces.2004.05.003 I. Jöbses, G. Egberts, K. Luyben & J. Roels, “Fermentation kinetics ofZymomonas mobilis at high ethanol concentrations: Oscillations in continuous cultures,” Biotechnol. Bioeng., vol. 28, no. 6, pp. 868–877, Jun. 1986. https://doi.org/10.1002/bit.260280614 A. Namjoshi & D. Ramkrishna, “Multiplicity and stability of steady states in continuous bioreactors: Dissection of cybernetic models,” Chem. Eng. Sci., vol. 56, no. 19, pp. 5593–5607, Oct. 2001. https://doi.org/10.1016/S0009-2509(01)00166-X Y. Zhang, A. Zamamiri, M. Henson & M. Hjortsø, “Cell population models for bifurcation analysis and nonlinear control of continuous yeast bioreactors,” J. Process Control, vol. 12, no. 6, pp. 721–734, Sep. 2002. https://doi.org/10.1016/S0959-1524(01)00010-5 G. Abdelghani, “Continuous Ethanol Fermentation at Very High Gravity in the Presence of Saccharomyces cerevisiae: A Bifurcation Analysis”, J. Sustain. Bioenergy Syst., vol. 8, pp. 116–126, Dec. 2018. https://doi.org/10.4236/jsbs.2018.84009 |
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Muñoz Ñungo , Oneida15e6c39a54b1177c2f765e91a69b440bMunoz, José Aldemar53d7a59ad09fb9e7a876baf698937c30300Hernández Sarabia, Héctor Mauriciob7abc75464d3a41fd4a77dbb9fa12fef2022-09-11 00:00:002024-04-09T20:21:39Z2022-09-11 00:00:002024-04-09T20:21:39Z2022-09-110122-6517https://hdl.handle.net/11323/12329https://doi.org/10.17981/ingecuc.18.2.2022.0310.17981/ingecuc.18.2.2022.032382-4700Introducción— Modelos de reactores anteriores han sido utilizados para estudiar el comportamiento dinámico de sistemas de producción de bioetanol, sin embargo, pocos han elaborado un estudio comparativo de estrategias de control que estabilicen y controlen las variables de interés. Objetivo— El objetivo del presente estudio es analizar la estabilidad de un sistema de fermentación para obtención de bioetanol, su comportamiento dinámico, la caracterización de puntos de equilibrio y puntos de bifurcación del modelo matemático planteado por Jarzebski en 1992 para una fermentación continua, teniendo en cuenta el rendimiento de la reacción en un biorreactor y la aplicación de técnicas de control industrial para su optimización. Metodología— Se utilizaron métodos de revisión y diseño de tipo cuantitativo y sistematizado. Resultados— Se presenta la comparación entre dos estrategias de control para controlar la producción de bioetanol, el control PID y el control Fuzzy. Se observó un mejor comportamiento dinámico cuando se utilizó el controlador Fuzzy. Conclusiones— Este trabajo muestra la importancia del análisis de estabilidad de un sistema en continuo y cómo éste puede definir las regiones de interés operativo, en este caso para la producción de etanol, mostrando que la productividad es inversamente proporcional a la tasa de dilución. Finalmente, se concluye que se tiene un mejor comportamiento dinámico del sistema cuando se utiliza un controlador Fuzzy.Introduction— Previous reactor models have been used to study the dynamic behavior of bioethanol production systems, however, few have elaborated a comparative study of control strategies that stabilize and control the variables of interest. Objective— The objective of this study is to analyze the stability of a fermentation system to obtain bioethanol, its dynamic behavior, the characterization of equilibrium points and bifurcation points of the mathematical model proposed by Jarzebski in 1992 for a continuous fermentation, taking into account the performance of the reaction in a bioreactor and the application of industrial control techniques for its optimization. Methodology— Review and design methods of quantitative and systematized type were used. Results— The comparison between two control strategies to control bioethanol production, PID control and Fuzzy. Conclusions— This work shows the importance of the stability analysis of a continuous system and how it can define the regions of operational interest, in this case for ethanol production, showing that productivity is inversely proportional to the dilution rate. Finally, it is concluded that a better dynamic behavior of the system is obtained when a Fuzzy controller is used. This work also shows the importance of the stability analysis of a continuous system and how it can define the regions of operational interest, in this case for the production of ethanol.application/pdftext/htmltext/xmlengUniversidad de la CostaINGE CUC - 2022http://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.http://purl.org/coar/access_right/c_abf2https://revistascientificas.cuc.edu.co/ingecuc/article/view/3555Alcoholic fermentationPID controlFuzzy controlnon-linear systems; stabilityfermentación alcohólicacontrol PIDcontrol Fuzzysistemas no linealesestabilidadAnálisis dinámico y comparación de técnicas de control en el proceso de obtención de bioetanolDynamic analysis and comparison of control techniques in the process of obtaining bioethanolArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Inge Cuc A. Jarzębski, “Modelling of oscillatory behaviour in continuous ethanol fermentation,” Biotechnol. Lett., vol. 14, no. 2, pp. 137–142, Feb. 1992. https://doi.org/10.1007/BF01026241 J. Sadhukhan, E. Martinez-Hernandez, M. Amezcua-Allieri, J. Aburto & J. Honorato, “Economic and environmental impact evaluation of various biomass feedstock for bioethanol production and correlations to lignocellulosic composition,” Bioresour. Technol. Reports, vol. 7, no. 1, pp. 1–10, Sep. 2019. https://doi.org/10.1016/j.biteb.2019.100230 B. Šantek, G. Gwehenberger, M. I. Šantek, M. Narodoslawsky & P. Horvat, “Evaluation of energy demand and the sustainability of different bioethanol production processes from sugar beet,” Resour. Conserv. Recycl., vol. 54, no. 11, pp. 872–877, Sep. 2010. https://doi.org/10.1016/j.resconrec.2010.01.006 P. Iodice, G. Langella & A. Amoresano, “Ethanol in gasoline fuel blends: Effect on fuel consumption and engine out emissions of SI engines in cold operating conditions,” Appl. Therm. Eng., vol. 130, pp. 1081–1089, Feb. 2018. https://doi.org/10.1016/j.applthermaleng.2017.11.090 J. Mantilla, D. Garzon & C. Galeano, “Análisis multivariable del desempeño y las emisiones en motores de combustión interna que utilizan mezclas de gasolina y etanol,” Ing. Energética, vol. 36, no. 3, pp. 232–242, Sep. 2015. Available: https://rie.cujae.edu.cu/index.php/RIE/article/view/451 República de Colombia. Superintendencia de Industria y Comercio, Resolución No. 40785 de 8 de julio de 2013, por la cual se concede un registro. Disponible en http://visordocs.sic.gov.co/documentos/Docs029/ActosEnLinea001/R-40785-2013.PDF?72 A. Yousefi-Darani, O. Paquet-Durand & B. Hitzmann, “Application of fuzzy logic control for the dough proofing process,” Food Bioprod. Process., vol. 115, pp. 36–46, May. 2019. https://doi.org/10.1016/j.fbp.2019.02.006 I. Edeh, “Bioethanol Production: An Overview,” in F. L. Inambao, Ed., Bioethanol Technologies, LDN, UK: IntechOpen, 2020. https://doi.org/10.5772/intechopen.94895 D. Bernier-Oviedo, J. Rincón-Moreno, J. Solanilla, J. Muñoz & H. Váquiro, “Comparison of two pretreatments methods to produce second-generation bioethanol resulting from sugarcane bagasse,” Ind. Crops Prod., vol. 122, pp. 414–421, Oct. 2018. https://doi.org/10.1016/j.indcrop.2018.06.012 M. Toor, S. Kumar, S. Malyan, N. Bishnoi, T. Mathmani, K. Rajedran & A. Pugazhendhi, “An overview on bioethanol production from lignocellulosic feedstocks,” Chemosphere, vol. 242, pp. 1–10, Mar. 2020. https://doi.org/10.1016/j.chemosphere.2019.125080 D. Maurya, A. Singla & S. Negi, “An overview of key pretreatment processes for biological conversion of lignocellulosic biomass to bioethanol,” 3 Biotech, vol. 5, no. 5, pp. 597–609, Feb. 2015. https://doi.org/10.1007/s13205-015-0279-4 N. Pachauri, A. Rani & V. Singh, “Bioreactor temperature control using modified fractional order IMC-PID for ethanol production,” Chem. Eng. Res. Des., vol. 122, pp. 97–112, Jun. 2017. https://doi.org/10.1016/j.cherd.2017.03.031 A. Ciesielski, & R. Grzywacz, “Dynamic bifurcations in continuous process of bioethanol production under aerobic conditions using Saccharomyces cerevisiae,” Biochem. Eng. J., vol. 161, pp. 1–10, Sep. 2020. https://doi.org/10.1016/j.bej.2020.107609 I. Pataro, M. da Costa, & B. Joseph, “Closed-loop dynamic real-time optimization (CL-DRTO) of a bioethanol distillation process using an advanced multilayer control architecture,” Comput. Chem. Eng., vol. 143, pp. 1–10, Dec. 2020. https://doi.org/10.1016/j.compchemeng.2020.107075E. Imamoglu & F. Sukan, “Scale-up and kinetic modeling for bioethanol production,” Bioresour. Technol., vol. 144, pp. 311–320, Sep. 2013. https://doi.org/10.1016/j.biortech.2013.06.118S. Fan, S, Chen, X. Tang, Z. Xiao, Q. Deng, P. Yao, Z. Sun, Y. Zhang & C. 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