A greenhouse climate model for control design

Su, Yuanping; Xu, Lihong

doi:10.1109/eeeic.2015.7165318

Cited by 8 publications

(6 citation statements)

References 8 publications

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“…Vanthoor is a well-structured explanatory model and its simulation performance has been extensively validated in European and North American greenhouses [17]. Vanthoor is actually a greenhouse environmental system model which includes a greenhouse microclimate model and a greenhouse crop growth model.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Yield Prediction Model for Greenhouse Tomato

Lin

Wei

2019

Agronomy

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The commonly used greenhouse crop yield prediction models today have their specific application scenarios, which may not ensure the accuracy of the results if the greenhouse environment changes. This greatly restricts their use in the greenhouse environment. To solve this problem, two widely used tomato growth models were compared in the study: TOMGRO and Vanthoor, and then an integrated model was obtained. Through the extended Fourier amplitude sensitivity test (EFAST), the model parameters were divided into three categories: optimized, fixed and ignored. In addition, Bayesian optimization was used as an optimization algorithm, through which the parameters applicable to the greenhouse can be optimized based on the greenhouse data. Compared with TOMGRO and Vanthoor, the output of the integrated model was more reasonable and universal, and the RMSE in the integrated model was 2.5974 while that in TOMGRO and Vanthoor both were over 17, reflecting the fact that the model output was closer to the actual value. According to the verification results of four-year greenhouse data, the model had high performance in predicting yield.

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Section: Introductionmentioning

confidence: 99%

An Integrated Yield Prediction Model for Greenhouse Tomato

Lin

Wei

2019

Agronomy

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“…The same model may be adopted for indoor farming also. The dynamic climate model of greenhouses, which involves microclimatic parameters, crop growth parameters, external climate parameters, control input parameters, and structural and materialistic parameters to determine the climatic condition is also adaptable for indoor environments [128,129]. In association with a nonlinear feedback controller, the Kalman filter removes sensor noise that corrupts the measured variables and processes noise that corrupts the system dynamics.…”

Section: Artificial Climate Controlmentioning

confidence: 99%

Smart Indoor Farms: Leveraging Technological Advancements to Power a Sustainable Agricultural Revolution

Hati

Singh

2021

AgriEngineering

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Conventional farming necessitates a large number of resources and infrastructure such as land, irrigation, manpower to manage farms, etc. Modern initiatives are required to automate conventional farms. Smart indoor farms offer the potential to remedy the shortfalls of conventional farms by providing a controlled, intelligent, and smart environment. This paper presents a three-dimensional perspective consisting of soilless farming, energy harvesting, and smart technologies, which could be considered as the three important characteristics of smart indoor farms. A six-layer smart indoor farms architecture has also been proposed, which explains how data are collected using various sensors and devices and then transmitted onto the cloud infrastructure for further analysis and control through various layers. Artificial lighting, smart nutrition management, and artificial climate control, to name a few, are some of the important requirements for smart indoor farms while considering control and service management factors. The major bottleneck in installing such systems is both the economical and the technical constraints. However, with the evolution of technology (and when they become widely available in the near future), a more favourable farming scenario may emerge. Furthermore, smart indoor farms could be viewed as a potential answer for meeting the demands of a sustainable agricultural revolution as we move closer to Agriculture 4.0. Finally, in order to adapt smart indoor farms and their study scope, our work has presented various research areas to potential researchers.

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“…Therefore, generally, an accurate system model, such as Vanthoor's model [26] and TOMGRO [29], is useful to improve the optimization performance. However, an accurate models are usually complex and computational expensive, a simple greenhouse climate model with 3 state variables, which was developed in our previous work [30] , was used to simulate the greenhouse climate in this work, and a reduced state TOMGRO developed by Jones [36] was used to simulate the crop growth. It should be pointed out that although the greenhouse system model is assumed to be accurate, the true energy consumption and crop yield may be still different from their predicted values, because the control system of the greenhouse climate cannot always ensure the controlled greenhouse climate to accurately track the setpoints.…”

Section: Experimental Settingmentioning

confidence: 99%