Temperature and humidity control system using fuzzy cognitive map

Intelligent Buildings have been more developed recently and tendency to be more intelligence is appeared. The intelligent buildings are the integration of four systems which are a Building Automation system (BAS), a Telecommunication of system (TS), an Office Automation system (OAS) and a computer aided facility management system (CAFMS). Building Automation system (BAS) is a main part of each intelligent building which is an integration of subsystems such as heating, ventilating and airconditioning system (HVAC), lighting control, automatic fire alarm system and security system. HVAC system is energy consuming. Increasing the nonlinearity and uncertainty in recent electrical and mechanical building’s structures cause description of the system become more difficult or impossible mathematically. The relationships among system’s inputs and outputs govern on the mathematical model of the system. Due to the nonlinearity of time-variability and multivariability of the HVAC system by disturbances and uncertainties, to design and implement the proper control strategy is a challenge. Therefore, dynamical model of the HVAC system should be used to apply different control methods to minimise energy consumption. This thesis is mainly focused on closed loop control of HVAC system to control the energy usage and synchronously balance with desired temperature and humidity ratio values. Hence, designing a nonlinear control procedure should be considered. The Fuzzy Cognitive Maps (FCMs) control method had been applied on the system. In order to reach the energy efficiency and desired temperature and humidity ratio values, the affecting and affected parameters are defined. The results of the FCM control shows that the controller stabilizes the outputs on the desired steady state with no overshoot and undershoots.

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