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An Innovative Adaptive Control System to Regulate Microclimatic Conditions in a Greenhouse

Author

Listed:
  • Giuseppina Nicolosi

    (Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna 94100, Italy)

  • Roberto Volpe

    (Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna 94100, Italy)

  • Antonio Messineo

    (Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna 94100, Italy)

Abstract

In the recent past home automation has been expanding its objectives towards new solutions both inside the smart home and in its outdoor spaces, where several new technologies are available. This work has developed an approach to integrate intelligent microclimatic greenhouse control into integrated home automation. Microclimatic control of greenhouses is a critical issue in agricultural practices, due to often common sudden daily variation of climatic conditions, and to its potentially detrimental effect on plant growth. A greenhouse is a complex thermodynamic system where indoor temperature and relative humidity have to be closely monitored to facilitate plant growth and production. This work shows an adaptive control system tailored to regulate microclimatic conditions in a greenhouse, by using an innovative combination of soft computing applications. In particular, a neural network solution has been proposed in order to forecast the climatic behavior of greenhouse, while a parallel fuzzy scheme approach is carried out in order to adjust the air speed of fan-coil and its temperature. The proposed combined approach provides a better control of greenhouse climatic conditions due to the system’s capability to base instantaneous solutions both on real measured variables and on forecasted climatic change. Several simulation campaigns were carried out to perform accurate neural network and fuzzy schemes, aimed at obtaining respectively a minimum forecasted error value and a more appropriate fuzzification and de-fuzzification process. A Matlab/Simulink solution implemented with a combined approach and its relevant obtained performance is also shown in present study, demonstrating that through controlled parameters it will be possible to maintain a better level of indoor climatic conditions. In the present work we prove how with a forecast of outside temperature at the next time-instant and rule-based controller monitoring of cooling or heating air temperatures and air velocities of devices that regulate the indoor micro-climate inside, a better adjustment of the conditions of comfort for crops is achievable.

Suggested Citation

  • Giuseppina Nicolosi & Roberto Volpe & Antonio Messineo, 2017. "An Innovative Adaptive Control System to Regulate Microclimatic Conditions in a Greenhouse," Energies, MDPI, vol. 10(5), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:722-:d:99152
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    4. Iddio, E. & Wang, L. & Thomas, Y. & McMorrow, G. & Denzer, A., 2020. "Energy efficient operation and modeling for greenhouses: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    5. Chan Kyu Lee & Mo Chung & Ki-Yeol Shin & Yong-Hoon Im & Si-Won Yoon, 2019. "A Study of the Effects of Enhanced Uniformity Control of Greenhouse Environment Variables on Crop Growth," Energies, MDPI, vol. 12(9), pages 1-24, May.
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