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

Farinaz Behrooz, Norman Mariun, Mohammad Hamiruce Marhaban, Mohd Amran Mohd Radzi and Abdul Rahman Ramli
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Farinaz Behrooz: Department of Electrical and Electronic Engineering, 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
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

Energies, 2018, vol. 11, issue 3, 1-41

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.

Keywords: nonlinear; MIMO; coupling effect; HVAC system; fuzzy cognitive map (FCM); soft computing method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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