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Non-linear control model for use in greenhouse climate control systems

Author

Listed:
  • Jalal Javadi Moghaddam
  • Ghasem Zarei

    (Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran)

  • Davood Momeni

    (Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran)

  • Hamideh Faridi

    (Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran)

Abstract

In this study, a non-linear control system was designed and proposed to control the greenhouse climate conditions. This control system directly uses the information of sensors, installed inside and outside the greenhouse. To design this proposed control system, the principles of a non-linear control system and the concepts of equilibrium points and zero dynamics of system theories were used. To show the capability and applicability of the proposed control system, it was compared with an integral sliding mode controller. A greenhouse with similar climatic conditions was used to simulate the performance of the integral sliding mode controller. In this study, it was seen that the integral sliding mode control system was more accurate; however, the actuator signals sent by this control system were not smooth. It could damage and depreciate the greenhouse equipment more quickly than the proposed non-linear control system. It was also shown that the regulation of the temperature and humidity was performed very smoothly by changing the reference signals according to the weather conditions outside the greenhouse. The ability of these two control systems was graphically demonstrated for temperature and humidity responses as well as for the signals sent to the actuators.

Suggested Citation

  • Jalal Javadi Moghaddam & Ghasem Zarei & Davood Momeni & Hamideh Faridi, 2022. "Non-linear control model for use in greenhouse climate control systems," Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 68(1), pages 9-17.
    • Handle: RePEc:caa:jnlrae:v:68:y:2022:i:1:id:37-2021-rae
    DOI: 10.17221/37/2021-RAE
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    References listed on IDEAS

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    1. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
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