A Greenhouse Temperature and Humidity Controller Based on MIMO Fuzzy System

Ying-chun, Kuang; Shen, Yue

doi:10.1109/isdea.2010.80

Cited by 8 publications

(3 citation statements)

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“…The so-called chemical treatment methods, that is, by the chemical methods, changing the chemical nature of the contaminants, so that it from the harmful conversion into harmless substances or can be Separation of substances, and then separated from the polluted water [5] .…”

Section: Chemical Methodsmentioning

confidence: 99%

Research Progress of Sewage Treatment Technology

Chen¹,

Wu²,

Xin³

et al. 2013

AMR

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Section: Chemical Methodsmentioning

confidence: 99%

Research Progress of Sewage Treatment Technology

Chen¹,

Wu²,

Xin³

et al. 2013

AMR

View full text Add to dashboard Cite

show abstract

“…A mathematical model that related the temperature gradient of the greenhouse with the duty cycle applied to the AC-AC converter for a heating system was defined by (1). Besides, the parametric variation of the plant temperature and the system uncertainty space were quantified for the design of the QFT controller temperature.…”

Section: A Mathematical Model Identificationmentioning

confidence: 99%

“…production rates, high quality, and low energy cost. In order to improve the efficiency of greenhouse crops, different strategies have been developed for temperature control since this variable strongly impacts the development of the plants [1]. One of these strategies is based on the development of algorithms that allow mitigating the effects of dead time when it is dominant on the process dynamics [2], according to the Smith predictor structures type for predictive control [3], modified Smith Predictor [4] and multivariable controllers for greenhouses [5].…”

Section: Introductionmentioning

confidence: 99%

Real-time QFT Control for Temperature in Greenhouses

Rodríguez

Corzo

2019

Maskay

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Sudden changes in a greenhouse environment negatively impact the development and production of crops, especially in greenhouses with natural ventilation when temperatures are low at night and change rapidly due to wet winds. To mitigate these variations, a design of a robust controller based on Quantitative Feedback Theory (QFT) as from a Smith predictor structure for the dead-time system is proposed. This structure offers high stability based on the gain margin, the phase margin, and the rejection of disturbances in the system output. This design was contrasted with a PID controller based on performance indices, according to the transient response and error in the presence of changes in the point of operation and charge disturbances. Final results showed that the dynamic response of the QFT controller improved compared to PID controller results.

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Energy efficiency optimization strategies for greenhouse‐based crop cultivation: A review

Kaur,

Sonawane,

Rosha

2023

Can J Chem Eng

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Worldwide, food scarcity is becoming a debatable concern among the scientific fraternity due to the increased populace, leading to decreased arable land. This has compelled us to explore various innovative and technological solutions, for example, large‐scale greenhouse farming, to meet the surging demand for field production. In this context, research efforts have been continually made by various scientists and researchers to explore more control strategies/algorithms for keeping the indoor climate comfortable and enhancing the greenhouse's energy effectiveness. Considering this, an initiative was made to summarize the documented research findings in the last decade focusing on energy‐efficient greenhouse‐based crop cultivation. The findings of some studies considering selective parametric conditions have been presented in graphs/tables for reader clarity and discussion. Initially, the studies on existing energy efficient strategies, parameters, monitoring systems, sensing networks, and control algorithms have been discussed. A state of the art review found that control strategies are essential in low‐energy greenhouses since they influence crop yield and cost. It was observed that advanced control algorithms and energy conservation in greenhouses received more attention due to wide spread application, high compatibility, low‐cost, and user‐friendly operations. In terms of future perspectives, it is anticipated that the development of machine learning, big data, and artificial intelligence, combining these technologies with traditional and advanced control strategies would lead to a revolution in the management of greenhouse energy.

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A Greenhouse Temperature and Humidity Controller Based on MIMO Fuzzy System

Cited by 8 publications

References 1 publication

Research Progress of Sewage Treatment Technology

Research Progress of Sewage Treatment Technology

Real-time QFT Control for Temperature in Greenhouses

Energy efficiency optimization strategies for greenhouse‐based crop cultivation: A review

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