The development of advanced closed‐loop irrigation systems requires accurate soil moisture information. In this work, we address the problem of soil moisture estimation for the agro‐hydrological systems in a robust and reliable manner. A nonlinear state‐space model is established based on the discretization of the Richards equation to describe the dynamics of the agro‐hydrological systems. We consider that model parameters are unknown and need to be estimated together with the states simultaneously. We propose a consensus‐based estimation mechanism, which comprises two main parts: (a) a distributed extended Kalman filtering algorithm used to estimate several model parameters; and (b) a distributed moving horizon estimation algorithm used to estimate the state variables and one remaining model parameter. Extensive simulations are conducted, and comparisons with existing methods are made to demonstrate the effectiveness and superiority of the proposed approach. In particular, the proposed approach can provide accurate soil moisture estimate even when poor initial guesses of the parameters and the states are used, which can be challenging to be handled using existing algorithms.

中文翻译：

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基于共识的农业水文学系统参数和状态估计方法

先进的闭环灌溉系统的开发需要准确的土壤湿度信息。在这项工作中，我们以一种可靠而可靠的方式解决了农业水文学系统中土壤水分估算的问题。基于理查兹方程的离散化，建立了一个非线性状态空间模型来描述农业水文学系统的动力学。我们认为模型参数未知，需要与状态同时进行估计。我们提出了一种基于共识的估计机制，该机制包括两个主要部分：（a）用于估计多个模型参数的分布式扩展卡尔曼滤波算法；（b）一种分布式移动视野估计算法，用于估计状态变量和一个剩余模型参数。进行了广泛的模拟，并与现有方法进行比较，以证明该方法的有效性和优越性。尤其是，即使使用了较差的参数和状态初始估计值，所提出的方法也可以提供准确的土壤湿度估算值，这很难通过现有算法来处理。