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Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps

Author

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  • Farinaz Behrooz

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia
    Centre for Advanced Power and Energy Research, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Norman Mariun

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia
    Centre for Advanced Power and Energy Research, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Mohammad Hamiruce Marhaban

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Mohd Amran Mohd Radzi

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Abdul Rahman Ramli

    (Department of Computer and Communication Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor, Malaysia)

Abstract

Heating, Ventilating, and Air Conditioning (HVAC) systems are the major energy-consuming devices in buildings. Nowadays, due to the high demand for HVAC system installation in buildings, designing an effective controller in order to decrease the energy consumption of the devices while meeting the thermal comfort demands in buildings are the most important goals of control designers. The purpose of this article is to investigate the different control methods for Heating, Ventilating, and Air Conditioning and Refrigeration (HVAC & R) systems. The advantages and disadvantages of each control method are discussed and finally the Fuzzy Cognitive Map (FCM) method is introduced as a new strategy for HVAC systems. The FCM method is an intelligent and advanced control technique to address the nonlinearity, Multiple-Input and Multiple-Output (MIMO), complexity and coupling effect features of the systems. The significance of this method and improvements by this method are compared with other methods.

Suggested Citation

  • Farinaz Behrooz & Norman Mariun & Mohammad Hamiruce Marhaban & Mohd Amran Mohd Radzi & Abdul Rahman Ramli, 2018. "Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps," Energies, MDPI, vol. 11(3), pages 1-41, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:495-:d:133530
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    References listed on IDEAS

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    3. Farinaz Behrooz & Norman Mariun & Mohammad Hamiruce Marhaban & Mohd Amran Mohd Radzi & Abdul Rahman Ramli, 2017. "A Design of a Hybrid Non-Linear Control Algorithm," Energies, MDPI, vol. 10(11), pages 1-32, November.
    4. Tashtoush, Bourhan & Molhim, M. & Al-Rousan, M., 2005. "Dynamic model of an HVAC system for control analysis," Energy, Elsevier, vol. 30(10), pages 1729-1745.
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