Abstract
This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the Supervisor-FCM model characteristics will be discussed. There is a going need for more autonomous and intelligent systems, especially in Complex Systems area, the application of Fuzzy Cognitive Maps for modeling the Supervisor may contribute to develop more sophisticated systems.