Laura Vélez-Landa1 ,
Carlos Manuel Astorga-Zaragoza2 ,
Héctor Ricardo Hernández de-León1 ,
Gloria Lilia Osorio-Gordillo2 ,
José Roberto Bermúdez-Hernández1
1 Tecnológico Nacional de México/Instituto Tecnológico de Tuxtla Gutiérrez; Tuxtla Gutiérrez, Chiapas, México.
2 Tecnológico Nacional de México/Centro Nacional de Investigación y Desarrollo Tecnológico; Cuernavaca, Morelos, México.
Abstract
En este artículo se presenta un diseño de observador no lineal para la estimación simultánea de parámetros y variables de estado. El caso de estudio son los cultivos de microalgas para la generación de biodiésel, donde las tasas de reacción, la concentración de biomasa, la cuota intracelular y la concentración de nitrógeno son variables críticas que proporcionan información sobre el estado del proceso. Sin embargo, estas variables pueden ser difíciles de medir debido a la falta de instrumentos específicos, al elevado costo de los sensores o a la inviabilidad de su instalación en el proceso. Por ello, en este artículo se presentan dos sensores virtuales basados en observadores como alternativa analítica para realizar la estimación de las principales variables o parámetros importantes del proceso: un observador no lineal adaptativo y un observador no lineal de alta ganancia. Los observadores se basan en el modelo matemático de Droop que describe la capacidad de las microalgas para almacenar nutrientes y el desacoplamiento entre la absorción de sustrato y el crecimiento de la biomasa. Se realizan simulaciones numéricas para evaluar el rendimiento de los observadores propuestos.
Traducción realizada con la versión gratuita del traductor www.DeepL.com/Translator
Vélez-Landa, L., Astorga-Zaragoza, C. M., Hernández de-León, H. R., Osorio-Gordillo, G. L., & Bermúdez-Hernández, J. R. (2019). Sensores virtuales basados en observadores para el monitoreo de cultivos de microalgas. Renewable Energy, Biomass & Sustainability, 1(1), 17–27. https://doi.org/10.56845/rebs.v1i1.5
📄Akash, P., Bharat, G., Pankaj, P., and Beena, P. (2017). Microalgae: antiquity to era of integrated technology. Renewable and Sustainable Energy Reviews, 71, 535-547.
📄Amalina N., Kee M., Uemura Y., Wei J. and Teong K. (2018). Harvesting and pre-treatment of microalgae cultivated in wastewater for biodiesel production: A review. Energy Conversion and Management, 171, 1416-1429.
📄Astorga-Zaragoza, C., Zavala-Río, A., Alvarado, V., Méndez-Ocaña, M. and Reyes-Reyes, J. (2007). Performance monitoring of heat exchangers via adaptive observers. Measurement, 40, 392-405.
📄Astorga-Zaragoza, C., Alvarado, V., Zavala-Río, A., Méndez, M., and Guerrero-Ramírez, G. (2008). Observer-based monitoring of heat exchangers. ISA Transaction, 47, 15-24.
📄Astorga-Zaragoza, C., Osorio-Gordillo, G., Reyes-Reyes, J., Madrigal-Espinosa, G. and Chadli, M. (2018). Takagi-Sugeno observers as an alternative to nonlinear observers for analytical redundancy. Application to a steam generator of a thermal power plant. International Journal of Fuzzy Systems, 20, 1756:1766.
📄Barreto, R. (2018). Fossil fuels, alternative energy and economic growth. Economic Modelling, 75, 196-220.
📄Benavides, M., Coutinho, D., Hantson, A., Van I.J., Vande Wouwer, A. (2015). Robust Luenberguer observers for microalgal cultures. Journal of Process Control, 36, 55-63.
📄Besançon, G. (2000). Remarks on nonlinear adaptive observer design. Systems & Control Letters, 41 (4), 271-280.
📄Bougaran G., Bernard O. and Sciandra A. (2010). Modeling continuous cultures of microalgae colimited by nitrogen and phosphorus. Journal of Theoretical Biology, 265 (3), 443-454.
📄Ching C., Chien H., Kao, H., Ping, H., Meng, W., Jo, C. (2015). Biodiesel production from wet microalgae feedstock using sequential wet extraction/transesterification and direct transesterification process. Bioresource Technology, 194, 179-186.
📄Chisti, Y. (2007). Biodiesel from microalgae. Biotechnology Advances, 25 (3), 294-306.
📄Chun, C., Kuei Y., Rifka A., Duu, L., and Jo, C. (2011). Cultivation, photobioreactor design and harvesting of microalgae for biodiesel production: a critical review. Bioresource Technology, 102 (1), 71-81.
📄Coutinho, D., Vargas, A., Feudjio, C., Benavides, M., and Vande W.A. (2019). A robust approach to the design of super-twisting observers-aplication to monitoring microalgae cultures in photo-bioreactors. Computers and Chemical Engineering, 121 (2), 46-56.
📄De Battista, H., Picó, J., Garelli F., and Vignoni, A. (2011). Specific growth rate estimation in (fed-) batch bioreactors using second-order sliding observers. Journal of Process Control, 21 (7), 1049-1055.
📄Demirbas A. and Fatih D.M. (2011). Importance of algae oil as a source biodiesel. Energy Conversion Management, 52, 163-170.
📄Demirbas, A, (2010). Use of algae as biofuel sources. Energy Conversion and Management, 51 (12), 2738-2749.
📄Dietzsch, C., Spadiut, O. and Herwig, C. (2011). A dynamic method based on the specific substrate uptake rate to set up a feeding strategy for Pichia pastoris. Microbial Cell Factories, 10 (14).
📄Deshmukh S., Kumar R., Bala K. (2019). Microalgae biodiesel: A review oil extraction, fatty acid composition, properties and effect on engine performance and emissions. Fuel Processing Technology, 191, 232-247.
📄Dochain, D. (2003). State and parameter estimation in chemical and biochemical processes: a tutorial. Journal of Process Control, 13 (8), 801-818.
📄Droop, M.R. (1983). 25 Years of algal growth kinetics: a personal view. Botánica Marina, 26 (3), 99-12.
📄Gauthier, P., Hammouri, H. and Othman, S. (1992). A simple observer for nonlinear systems application to bioreactors. IEEE Transactions on Automatic Control, 37 (6), 875-880.
📄Jenzsch, M., Simutis, R. and Luebbert, A. (2006). Generic model control of the specific growth rate in recombinant Escherichia coli cultivations. Journal of Biotechnology,122 (4), 483-493.
📄Leonard M., Michaelides E. and Michaelides D. (2020). Energy storage needs for the substitution of fossil fuel power plants with renewables. Renewable Energy, 145, 951-962.
📄Mohd, A., Ha N., Hussain, A., Dochain, D, (2015). Review and classification of recent observers applied in chemical process systems. Computers and Chemical Engineering, 76, 27-41.
📄Mohammad, G. (2018). Microalgae: Prospects for Greener future buildings. Renewable and Sustainable Energy Reviews, 81, 1175-1191.
📄Mohammadmatin, H., Mohammad-Hossein, S., Zahra, N., Omid, T., and Hamid, F. (2018). Technical, economic and energy assessment of an alternative strategy for mass production of biomass and lipid from microalgae. Journal of Environmental Chemical Engineering, 6 (1), 866-873.
📄Nuñez, S., De Battista, H., Garelli, H., Vignoni, A., and Picó, J. (2013). Second-order sliding mode observer for multiple kinetic rates estimation in bioprocesses. Control Engineering Practice, 21 (9), 1259-1265.
📄Ortiz-Torres G., Escobar-Jiménez R., Adam-Medina M., Sánchez-Coronado M., Astorga-Zaragoza C., Olivares-Peregrino V. and Téllez-Anguiano A. (2013). Detección y diagnóstico de fallas en sensores aplicado a una columna de destilación mediante un observador adaptable. En Congreso Nacional de Control Automático, Ensenada, Baja California, México.
📄Rincón, L., Jaramillo, C. and Cardona, C. (2014). Comparision of feedstocks and technologies for biodiesel production: An environmental and techno-economic evaluation. Renewable Energy, 69, 479-487.
📄Shih, H., Shu, H., Chun, Y., Tomohisa, H., Akihiko, K., Jo, C. (2013). Characterization and optimization of carbohydrate production from and indigenous microalga Chlorella vulgaris FSP-E. Bioresource Technology, 135, 157-165.
📄Solimeno, A., Acién, G. and García J. (2017). Mechanistic model for design, analysis, operation and control of microalgae cultures: Calibration and application to tubular photobioreactors. Algal Research, 21, 236-246.
📄Spolaore, P., Claire Joannis-Cassan, E., and Arsène, I, (2006). Commercial applications of microalgae. Journal of Bioscience and Bioengineering, 101 (2), 87-96.
📄Téllez-Anguiano A., Astorga-Zaragoza, C., Targui, B., Aguilera-González, A., Reyes-Reyes, J. and Adam-Medina, M. (2009). Experimental validation of a high-gain observer for composition estimation in an etanol-water distillation column. Asia-Pacific Journal Chemical Engineering, 4 (6), 942-952.
📄Uganeeswary, S., Man L., Yoshimitsu, U., Jun, L., Keat, L., and Siew, S. (2019). Insights into the microalgae cultivation technology and harvesting process for biofuel production: a review. Renewable and Sustainable Energy Reviews, 115, 109-361.
📄Velez-Landa, L., Hernández, H., Astorga-Zaragoza, C., Bermúdez, J., López-Estrada, F. and Adam-Medina, M. (2019). Observador adaptable para la estimación simultánea de parámetros en cultivos de microalgas. En 3ª Jornada de Ciencia y Tecnología Aplicada, Cuernavaca Morelos, México.
📄Vojinovi, V., Cabral, J., and Fonseca, L. (2006). Real-time bioprocess monitoring. Part I: in situ sensors. Sensors and Actuators B: Chemical, 114, 1083–1091.
📄Yoo J., Kim H. and Lee M. (2014). Dynamic modelling of mixotrophic microalgal photobioreactor systems with time-varying yield coefficient for the lipid consumption. Bioresource Technology, 162, 228-235.
📄Yuan S., Zhou X., Chen R. and Song B. (2014). Study on modelling microalgae growth in nitrogen-limited culture system for estimating biomass productivity. Renewable and Sustainable Energy Review, 34, 525-535.
,
Héctor Ricardo Hernández de-León1