In this paper, an intelligent controller based on a novel self-tuning fuzzy logic framework for elevator control applications is presented. The proposed controller utilizes the measured performance data of the elevator control system i.e. average waiting time (AWT), to initiate self-tuning through the adjustment of the membership functions, and the modification of the rule set. The controller's adaptation to the system's environment that is based on the system's measured performance eliminates the heavy dependence on the predicted traffic patterns for adaptation. From computer simulation, the controller's effectiveness is satisfactorily verified.