  The typical agricultural irrigation scheduler provides information on how
much to irrigate and when to irrigate. The accurate and effective scheduler
decision for a large agricultural field is still an open research problem. In
this work, we address the high dimensionality of the agricultural field and
propose a systematic approach to provide optimum irrigation amount and
irrigation time for three-dimensional agro-hydrological systems. The water
dynamics of the agro-hydrological system are represented using a cylindrical
three-dimensional Richards Equation. We introduce a structure-preserving model
reduction technique to decrease the dimension of the system model. Using the
reduced model, the optimization-based closed-loop scheduler is designed in
model predictive control (MPC) environment. The closed-loop approach can handle
weather disturbances and provide improved yield and water conservation. The
primary objective of the proposed scheduler is to ensure maximum yield, minimum
water consumption and maximize the time between the two irrigation events,
which results in less electricity usage. The proposed approach is applied to
three different scenarios to show the effectiveness and superiority of the
proposed framework.

Systems and Control;Systems and Control