Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse

Chen, Wei-Han; Mattson, Neil S.; You, Fengqi

doi:10.1016/j.apenergy.2022.119334

Cited by 38 publications

(6 citation statements)

References 55 publications

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“…External weather plays a crucial role in greenhouse temperature control. In this paper, two temperature setting points (daytime and nighttime) are set because of the large temperature difference between day and night [39]. Then, an S-shaped function is used to smooth the conversion between the two levels, which avoids the control input sudden change or saturation.…”

Section: System Parameters and Disturbance Settingsmentioning

confidence: 99%

Design of MFAC greenhouse temperature controller based on LESO with disturbance estimation and fuzzy controller with parameter tuning

Wang,

Li,

et al. 2024

Phys. Scr.

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Greenhouse agriculture has become an essential part of modern agriculture. The proper temperature is essential for greenhouse crops. Therefore, it is necessary to determine an appropriate greenhouse temperature automatic control strategy for greenhouse environment control. A model-free adaptive greenhouse temperature control strategy is proposed by combining a linear extended state observer and a fuzzy controller. Specifically, the linear extended state observer is introduced to estimate model approximation error generated by pseudo gradient estimation. The fuzzy controller is used to correct the system parameter online. In the absence of disturbances, compared with the typical model-free adaptive scheme, the MAE and RMSE of the proposed scheme are reduced by 57.55 % and 5.40 %, respectively. In the presence of custom disturbances, the proposed control scheme still has a faster response speed, stronger robustness, and higher control accuracy. And the proposed method can reduce the frequent action of the actuator, thus effectively reducing the energy cost.

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Section: System Parameters and Disturbance Settingsmentioning

confidence: 99%

Design of MFAC greenhouse temperature controller based on LESO with disturbance estimation and fuzzy controller with parameter tuning

Wang,

Li,

et al. 2024

Phys. Scr.

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“…In addition, the temperature and relative humidity of a certain layer in the greenhouse were the average values of 9 groups at the layer. The light rate in the greenhouse was calculated by Equation (1).…”

Section: Experimental Materialsmentioning

confidence: 99%

“…Hainan's tropical climate, with high temperatures and humidity and heavy storms in the summer, greatly limits open-field cultivation, so it is of great significance to develop tropical greenhouses in this area. Greenhouse plant quality and yield are affected by environmental factors [1], and the indoor environment of greenhouses is unevenly distributed [2]. In order to ensure the intensive production of plants, it is necessary to regulate the greenhouse environment to meet the growth needs of plants [3].…”

Section: Introductionmentioning

confidence: 99%

CFD Analysis and Optimization of a Plastic Greenhouse with a Semi-Open Roof in a Tropical Area

Yin,

Wang,

Zeng

et al. 2024

Agronomy

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A numerical simulation model of a natural ventilation greenhouse is helpful for improving the production and quality of greenhouse crops in tropical areas. Field experiments show that the mean coefficient of variation of indoor light intensity in four seasons was lower than 10.0%. The highest indoor temperature reached 39.3 °C during summer, while the average indoor temperature ranged from 24 °C to 26 °C in the other three seasons. The average relative humidity in the greenhouse ranged from 76% to 87% annually, which was higher and more stable than that in the external environment. A three-dimensional steady-state numerical model of the greenhouse was established based on computational fluid dynamics. Under natural ventilation conditions, the maximum error between the simulated value and the measured value of the temperature in each measuring point was 5.90%. And the average relative error between the simulated and measured values was 3.0% in the range of 0.7 m−1.5 m of crop cultivation height. Finally, a numerical simulation of adding side windows and expanding the vents was carried out. The results show that these methods can homogenize the airflow distribution in the greenhouse and improve the utilization efficiency of natural ventilation without more mechanical system operations.

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“…The smart greenhouse described by [66] and [67] is suitable for various crops, including tomatoes, and has shown positive effects on the growth of begonia, tomatoes, and peppers. During the observation period, the system used only 2800 mL of water when needed, indicating efficient water usage.…”

Section: B Case Studies On Tomato Cultivation In An Smart Greenhouse ...mentioning

confidence: 99%

A Study of Irrigation Management in Smart Farming and IoT for Greenhouse Tomato Production

Awang Bono ,Roni Kastaman , Edy Suryadi , Yanti Rubiyanti

2024

jes

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In this study of the relevant literature, we look at the development of smart farming and precision agriculture in greenhouse tomato cultivation, paying particular attention to the role that the Internet of Things (IoT) and automated irrigation systems have played thus far. Five terms were used to compile this literature review: automated watering systems, greenhouses, the Internet of Things, tomatoes, and smart farming. This article summarizes recent advancements in smart farming tech, their impact on greenhouse tomato farming, and their potential to boost future crop yield and quality. The evaluation starts by introducing 'smart farming' and its significance in agriculture, followed by a review of the greenhouse sector and an overview of the Internet of Things (IoT) within it, with subsequent examination of the pros and cons of employing smart farming and IoT in greenhouse tomato cultivation through specific industry technology examples. The following overview section discusses the benefits of cultivating tomatoes in a smart greenhouse, techniques for achieving optimal results in greenhouse tomato farming, and includes case studies to demonstrate the advantages of automated irrigation for smart greenhouse tomato cultivation, while this literature review analyzes the current state of innovative farming technology and its effect on greenhouse tomato cultivation, covering smart farming, greenhouse cultivation, the Internet of Things, tomato cultivation, and automated irrigation, summarizing significant results and recommendations for future research, including promising increases in crop yield and quality.

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Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse

Cited by 38 publications

References 55 publications

Design of MFAC greenhouse temperature controller based on LESO with disturbance estimation and fuzzy controller with parameter tuning

Design of MFAC greenhouse temperature controller based on LESO with disturbance estimation and fuzzy controller with parameter tuning

CFD Analysis and Optimization of a Plastic Greenhouse with a Semi-Open Roof in a Tropical Area

A Study of Irrigation Management in Smart Farming and IoT for Greenhouse Tomato Production

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