基于Hamilton-Jacobi-Bellman方程的作物灌溉最优控制

J. Ramanathan, Yuting Chen, P. Cournède
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引用次数: 1

摘要

由于全球水资源短缺问题日益严重,农业用水管理是一个关键问题。基于植物生长与水资源相互作用的动态模型的最新进展,我们的目标是研究作物灌溉的最优控制问题。为此,我们首先描述了甜菜生长的LNAS模型,该模型驱动了植物生物量和土壤水分储备的动态。然后引入与农民利润相对应的效用函数,并由哈密顿-雅可比-贝尔曼(HJB)方程推导出价值函数。然后采用逆向有限差分格式求解HJB方程。在适当的Courant-Friedrichs-Lewy条件下证明了离散化步骤是收敛的。给出了一些数值模拟来说明这种解析度。
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Optimal Control of Crop Irrigation based on the Hamilton-Jacobi-Bellman Equation
Water management in agriculture is a key issue due to the increasing problem of water scarcity worldwide. Based on the recent progress in the dynamic modeling of plant growth in interaction with the water resource, our objective is to study the optimal control problem of crop irrigation. For this purpose, we first describe the LNAS model for sugar beet growth, driving the dynamics of both plant biomass and soil water reserve. We then introduce the utility function corresponding to the farmer’s profit and derive the value function from the Hamilton-Jacobi-Bellman (HJB) equation. Then a backward finite-difference scheme is implemented to solve the HJB equation. It is proved to converge under a proper Courant-Friedrichs-Lewy condition for the discretization step. A few numerical simulations are provided to illustrate the resolution.
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