dc.creator | Cáceres Rodríguez, Gabriela Belén | es |
dc.creator | Pereira Martín, Mario | es |
dc.creator | Millán Millán, Pablo Manuel | es |
dc.date.accessioned | 2024-01-17T11:11:37Z | |
dc.date.available | 2024-01-17T11:11:37Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Cáceres Rodríguez, G.B., Pereira Martín, M. y Millán Millán, P.M. (2022). Economic model predictive control for interactions of water sources connected crop field. IFAC-Papers OnLine, 55 (32), 194-199. https://doi.org/10.1016/j.ifacol.2022.11.138. | |
dc.identifier.issn | 2405-8963 | es |
dc.identifier.uri | https://hdl.handle.net/11441/153502 | |
dc.description.abstract | Interest in predicting and optimizing irrigation to minimize water usage in agriculture is growing. In this paper, we present how different water sources interconnected in a farm (surface and underground reservoirs) can provide the optimal amount of water to the crop, considering the water available in each water source and the energy cost associated with pumping, without compromising the crop yield. For this purpose, the formulated economic Model Predictive Control makes use of the dynamical non-linear agro-hydrological model, considering the Volumetric Water Content (VWC) at different depths of the soil and the mass balance of the surface reservoir to generate optimal interactions and flow control strategies from the water sources to the crop field to meet future irrigation demands and finally consider the use of these water sources to alleviate the effects of environmental changes and water scarcity. | es |
dc.format | application/pdf | es |
dc.format.extent | 6 p. | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | IFAC-Papers OnLine, 55 (32), 194-199. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Predictive control | es |
dc.subject | Irrigation | es |
dc.subject | Optimizing | es |
dc.title | Economic model predictive control for interactions of water sources connected crop field | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Proyectos Arquitectónicos | es |
dc.relation.projectID | Grant 2020/ACDE/000192 | es |
dc.relation.projectID | PY20-RE-017-LOYOLA | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S2405896322027719?via%3Dihub | es |
dc.identifier.doi | 10.1016/j.ifacol.2022.11.138 | es |
dc.contributor.group | Universidad de Sevilla. HUM958: In-Gentes [investigación en Generación de Territorios] | es |
dc.journaltitle | IFAC-Papers OnLine | es |
dc.publication.volumen | 55 | es |
dc.publication.issue | 32 | es |
dc.publication.initialPage | 194 | es |
dc.publication.endPage | 199 | es |
dc.contributor.funder | Agencia Española de Cooperación Internacional para el Desarrollo (AECID) | es |
dc.contributor.funder | Junta de Andalucía | es |