PACHECO VIANA, ERID EULOG, Pérez E. , SALVADOR ORTIZ, JOSÉ RAMÓN, MILLÁN GATA, PABLO
No
European Control Conf., ECC
Conference Paper
Científica
01/01/2024
2-s2.0-85200576223
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.
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