Hybrid Nonlinear Controller Design for Air Conditioning System

In this study, a nonlinear, intelligent and robust controller with a simple algorithm has been applied to the airconditioning system. The hybrid control algorithm is based on Fuzzy Cognitive Map (FCM) method which uses the Generalized Predictive Control (GPC) method controller to define the initial weights of FCM controller. The proposed controller performance proved that the Fuzzy Cognitive Map-Generalized Predictive Control controller is suitable for Multiple-Input and Multiple-Output nonlinear system of an air-conditioning system and an optimum thermal comfort condition was obtained using the proposed control algorithm. Finally, the Fuzzy Cognitive Map-Generalized Predictive Control controller shows a successful results and applicable control design approach to the Nonlinear Multiple-Input and Multiple-Output air-conditioning system. This system managed to achieve desired temperature at 700 seconds with 0% error and desired humidity at 900 seconds with 5% error from 50% humidity.