Advanced Control by Reinforcement Learning for Wastewater Treatment Plants: A Comparison with Traditional Approaches

Hernández-del-Olmo, Félix, Gaudioso, Elena, Duro, Natividad, Dormido, Raquel y Gorrotxategi, Mikel . (2023) Advanced Control by Reinforcement Learning for Wastewater Treatment Plants: A Comparison with Traditional Approaches. Applied Sciences, Vol. 13(8), pÆg. 4752

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Título Advanced Control by Reinforcement Learning for Wastewater Treatment Plants: A Comparison with Traditional Approaches
Autor(es) Hernández-del-Olmo, Félix
Gaudioso, Elena
Duro, Natividad
Dormido, Raquel
Gorrotxategi, Mikel
Materia(s) Ingeniería Informática
Abstract Control mechanisms for biological treatment of wastewater treatment plants are mostly based on PIDS. However, their performance is far from optimal due to the high non-linearity of the biological and changing processes involved. Therefore, more advanced control techniques are proposed in the literature (e.g., using artificial intelligence techniques). However, these new control techniques have not been compared to the traditional approaches that are actually being used in real plants. To this end, in this paper, we present a comparison of the PID control configurations currently applied to control the dissolved oxygen concentration (in the active sludge process) against a reinforcement learning agent. Our results show that it is possible to have a very competitive operating cost budget when these innovative techniques are applied.
Palabras clave advanced control
reinforcement learning
wastewater system
Editor(es) MDPI
Fecha 2023
Formato application/pdf
Identificador bibliuned:95-Fhernandez-0001
http://e-spacio.uned.es/fez/view/bibliuned:95-Fhernandez-0001
DOI - identifier https://doi.org/10.3390/app13084752
ISSN - identifier 2076-3417
Nombre de la revista Applied Sciences
Número de Volumen 13
Número de Issue 8
Publicado en la Revista Applied Sciences, Vol. 13(8), pÆg. 4752
Idioma eng
Versión de la publicación publishedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto
Notas adicionales The registered version of this article, first published in Applied Sciences, is available online at the publisher's website: MDPI, https://doi.org/10.3390/app13084752
Notas adicionales La versión registrada de este artículo, publicado por primera vez en Applied Sciences, está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/app13084752

 
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Creado: Thu, 25 Jan 2024, 21:37:01 CET