Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques
This paper presents a black-box dynamic model for microalgae production in raceway reactors. The black-box model, developed using Deep Learning techniques, allows the estimation of the pH in a 100 m2 raceway reactor. The model has been created using only and exclusively data, what gives a high ease...
| Main Authors: | , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
2022
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| Online Access: | http://hdl.handle.net/10835/13624 |
| _version_ | 1789406654635180032 |
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| author | Otálora, Pablo Guzmán, José Luis Berenguel, Manuel Acién Fernández, Francisco Gabriel |
| author_facet | Otálora, Pablo Guzmán, José Luis Berenguel, Manuel Acién Fernández, Francisco Gabriel |
| author_sort | Otálora, Pablo |
| collection | DSpace |
| description | This paper presents a black-box dynamic model for microalgae production in raceway reactors. The black-box model, developed using Deep Learning techniques, allows the estimation of the pH in a 100 m2 raceway reactor. The model has been created using only and exclusively data, what gives a high ease of use. The results obtained verify the effectiveness of this type of techniques for the modelling of complex dynamic processes. The model was validated for different weather conditions obtaining satisfactory results. Thus, the obtained model is fairly useful for simulation purposes or for the implementation of model-based control techniques. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-13624 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2022 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-136242023-10-10T09:50:22Z Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques Otálora, Pablo Guzmán, José Luis Berenguel, Manuel Acién Fernández, Francisco Gabriel This paper presents a black-box dynamic model for microalgae production in raceway reactors. The black-box model, developed using Deep Learning techniques, allows the estimation of the pH in a 100 m2 raceway reactor. The model has been created using only and exclusively data, what gives a high ease of use. The results obtained verify the effectiveness of this type of techniques for the modelling of complex dynamic processes. The model was validated for different weather conditions obtaining satisfactory results. Thus, the obtained model is fairly useful for simulation purposes or for the implementation of model-based control techniques. 2022-04-19T11:34:49Z 2022-04-19T11:34:49Z 2020-09-19 info:eu-repo/semantics/article http://hdl.handle.net/10835/13624 en http://eu-repo/grantAgreement/ES/MINECO/2016SABANA/ES/Sustainable%20Algae%20Biorefinery%20for%20Agriculture%20aNd%20Aquaculture/SABANA/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | Otálora, Pablo Guzmán, José Luis Berenguel, Manuel Acién Fernández, Francisco Gabriel Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques |
| title | Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques |
| title_full | Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques |
| title_fullStr | Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques |
| title_full_unstemmed | Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques |
| title_short | Dynamic Model for the pH in a Raceway Reactor using Deep Learning techniques |
| title_sort | dynamic model for the ph in a raceway reactor using deep learning techniques |
| url | http://hdl.handle.net/10835/13624 |
| work_keys_str_mv | AT otalorapablo dynamicmodelforthephinaracewayreactorusingdeeplearningtechniques AT guzmanjoseluis dynamicmodelforthephinaracewayreactorusingdeeplearningtechniques AT berenguelmanuel dynamicmodelforthephinaracewayreactorusingdeeplearningtechniques AT acienfernandezfranciscogabriel dynamicmodelforthephinaracewayreactorusingdeeplearningtechniques |