Abstract
This paper investigated the implementing of soft computing methodology of fuzzy cognitive map on controlling parameters of heating, ventilating and air-conditioning systems. In the past few years, many researches have been done on application of different controllers on heating, ventilating and air-conditioning system as a more energy consuming part of the building automation system. Unlike the conventional control methods which are used more in this area like PID controller, the fuzzy cognitive maps method was chosen to control of the temperature and humidity of the room in winter operation season and summer operation season. By applying the fuzzy cognitive map controller, more energy efficiency and also more energy saving has obtained. The advantages of using fuzzy cognitive maps indicated as a controller on the typical heating, ventilating and air-conditioning system in this paper. The algorithm of FCM control reached to the goals of comfort, robustness and energy saving. Key words: Fuzzy cognitive map, heating ventilating and air-conditioning system, energy saving, energy efficiency, robustness.
Highlights
The heating, ventilating and air-c onditioning (HVA C) system is the more energy consuming part of t he building automation systems (BAS) in t he int elligent buildings
The simulation results by MATLAB software show the comparison of the P ID controller which is used in Tashtoush et al (2005) with Fuzzy Cognitive Map (FCM) controller for controlled variables of zone temperature and zone humidity respectively and for control variables supply air temperature and supply humidity ratio respectively
The comparisons of the Fuzzy Cognitive Maps method to control versus PID controller have been done
Summary
The heating, ventilating and air-c onditioning (HVA C) system is the more energy consuming part of t he building automation systems (BAS) in t he int elligent buildings. Due to the limited sources of energy in the world and fuel crisis, designing the better controllers to saving energy and energy efficiency is more important challenging for control engineers (Tachwali et al, 2007). Due t o the great impact of HVACs systems on power and energy consumption, knowing the structure and operation of HVAC systems are possessing importance
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