Model predictive control for precision irrigation of a Quinoa crop

Abstract Traditional High Andean agriculture is rainfed, and irrigation commonly carried out in an open loop, that is, without measuring variables such as soil moisture content or plant development to define water consumption. This article presents model predictive control applied systems under real conditions, whose purpose the efficient use of rainfed crops with improved yield crop productivity at minimum The a strategy applying calculates optimal amount for daily conditions. most important attraction prediction future behavior controlled function changes manipulated variables. objective improve consumption, this, it will be necessary models link Aquacrop software allow source data, values. controller evaluated Quinoa ( Chenopodium Willdenow ), performance compared against existing traditional data literature. results indicate can achieve higher efficiency reduce supplies considerably.