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

TLDR

HVAC systems are the largest energy consumers in buildings, and reducing their consumption while maintaining thermal comfort is a key objective for control designers. This article investigates various control methods for HVAC and refrigeration systems. The authors review the pros and cons of existing control strategies and present the Fuzzy Cognitive Map (FCM) approach, an intelligent technique that handles nonlinearity, MIMO, complexity, and coupling. The FCM method demonstrates superior performance and improvements over other control techniques.

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.