Model-predictive control of irrigation - a case study in India

作     者：Dilpreet Singh Sankaranarayanan Subramanian Sebastian Engell 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2023年第56卷第2期

页      面：9912-9917页

主　　题：modeling and control of agriculture model predictive and optimization-based control precision agriculture 

摘      要：Agriculture is a major consumer of freshwater, in particular in countries like India. From the perspectives of crop yield and water conservation, the development of advanced model-based irrigation scheduling methods is desirable. Most of the farming in India is done by small-scale farmers and to serve their needs, we are developing a simple model-based system that can be applied semi-manually and does not need expensive sensors and costly data. In this article, an optimal irrigation system, based on Model Predictive Control (MPC), which uses a physics-based model to compute an optimal amount of irrigation for the next day, is developed. The robustness of the developed system is tested by comparing the effect of errors in a key model parameter as well as in the weather forecast.