灌溉渠高效稳健控制的综合数学模型

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-05-20 DOI:10.1016/j.envsoft.2024.106083
Rajani Pandey , G R Jayanth , M.S Mohan Kumar
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引用次数: 0

摘要

以线性控制为导向的模型对于表示水渠动态以设计控制器非常重要。本研究侧重于水力控制结构(闸门)建模,以解决灌溉渠道固有的复杂的相互依存行为。针对单水池和多水池情况,引入了一个综合数学模型,将水位与闸门开启结合起来,以模拟排水量。所提出的模型捕捉到了渠池内部和渠池之间的水力耦合,这是一项重要发现。该模型在三条不同运河的均匀和非均匀流量下进行了广泛评估,突出了模型对各种系统的适用性。此外,还针对不同的运行条件和水力参数,对标称模型中固有的不确定性进行了评估。建议的模型与现有模型和圣弗南(SV)模型进行了比较,结果显示水位预测的准确性有所提高。水力模型的这一进步有助于开发适应性强的运河模型,这对开发稳健的控制器以加强灌溉渠道的水管理至关重要。
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Comprehensive mathematical model for efficient and robust control of irrigation canals

Linear control-oriented models are important to represent canal dynamics for designing controllers. This study focuses on hydraulic control structure (gate) modelling to address the complex interdependent behavior inherent in irrigation canals. A comprehensive mathematical model that incorporates the water level with gate-opening to model discharge is introduced for single and multiple canal pool scenarios. The proposed model captures the hydraulic coupling within and among canal pools, a key finding. The model is evaluated extensively under uniform and non-uniform flows across three distinct canals, highlighting the model's applicability to various systems. The uncertainty inherent within the nominal model is also assessed for varying operating conditions and hydraulic parameters. The proposed model is compared with the existing and the Saint-Venant (SV) model, showing improved accuracy in water-level predictions. This advancement in hydraulic modelling contributes to adaptable canal models essential in developing robust controllers to enhance water management in irrigation canals.

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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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