Título Exploring the Capabilities of Adaptive Model Predictive Control in Irrigation Systems
Autores PACHECO VIANA, ERID EULOG, Pérez E. , SALVADOR ORTIZ, JOSÉ RAMÓN, MILLÁN GATA, PABLO
Publicación externa No
Medio 2024 European Control Conference, Ecc 2024
Alcance Conference Paper
Naturaleza Científica
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200576223&doi=10.23919%2fECC64448.2024.10591156&partnerID=40&md5=9e3698d2ce0d1ad97b4f01db38327790
Fecha de publicacion 01/01/2024
Scopus Id 2-s2.0-85200576223
DOI 10.23919/ECC64448.2024.10591156
Abstract This work addresses the problem associated with the variability of the parameters involved in irrigation control systems for real crops. Factors such as soil compaction, climatic variability or phenological state of the crops, among others, significantly influence the dynamics of these systems, challenging the implementation of model-based controllers in real use cases. In this context, an Adaptive Model Predictive Control scheme is proposed, which makes it possible to update the model by employing a recursive system identification. A comparison with a conventional predictive controller employing a constant model is made. The study is based on models identified from data collected in a production farm in Seville, Spain. The validation of the proposed strategy and the comparison between the adaptive MPC and the conventional MPC are performed by means of simulations. The results demonstrate the potential applicability and effectiveness of Adaptive MPC in real farming conditions. © 2024 EUCA.
Palabras clave Adaptive control systems; Controllers; Irrigation; Model predictive control; Predictive control systems; Soil mechanics; Adaptive model predictive control; AS-soils; Climatic variability; Control schemes; Irrigation controls; Irrigation systems; Model-based controller; Predictive controller; Soil compaction; System-identification; Crops
Miembros de la Universidad Loyola

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