| Título |
Economic Model Predictive Control for Smart and Sustainable Farm Irrigation |
| Autores |
CÁCERES RODRIGUEZ, GABRIELA BELÉN, MILLÁN GATA, PABLO, PEREIRA MARTÍN, MARIO, Lozano D. |
| Publicación externa |
No |
| Medio |
2021 European Control Conference, Ecc 2021 |
| Alcance |
Conference Paper |
| Naturaleza |
Científica |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124900410&doi=10.23919%2fECC54610.2021.9655201&partnerID=40&md5=79828c5e3287c813db1b9a9503e34dab |
| Fecha de publicacion |
01/01/2021 |
| ISI |
000768455200185 |
| Scopus Id |
2-s2.0-85124900410 |
| DOI |
10.23919/ECC54610.2021.9655201 |
| Abstract |
The joint effects of rise of global population, climate change and water scarcity makes the shift towards an efficient and sustainable agriculture more and more urgent. Fortunately, recent developments in low-cost, IoT-based sensors and actuators can help us to incorporate advanced control techniques for efficient irrigation system. This paper proposes the use of an economic model predictive control at a farm scale. The controller makes use of soil moisture data sent by the sensors, price signals, operative restrictions, and accurate dynamical models of water dynamics in the soil. Its performance is demonstrated through simulations based on a real case-study, showing that it is possible to obtain significant reductions in water and energy consumption and operation costs. © 2021 EUCA. |
| Palabras clave |
Climate change; Costs; Economics; Energy utilization; Irrigation; Soil moisture; Advanced control; Economic models; Economic optimization; Global population; Joint effect; Low-costs; Model-predictive control; Sensors and actuators; Sustainable agriculture; Water scarcity; Model predictive control |
| Miembros de la Universidad Loyola |
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