Development of a self-tuning fuzzy logic controller for intelligent control of elevator systems
The search for an intelligent group controller that can satisfy multi-criteria requirements of an elevator group control system has become a great challenge for researchers. This paper presents the development of an elevator group controller based on fuzzy logic framework with a self-tuning scheme. Instead of basing on predicted traffic patterns to initiate modifications in the control outputs produced, the proposed group controller utilizes average waiting time (AWT) as the measured performance criterion used to adjust the membership functions and to select appropriate fuzzy rule sets, for the generation of suitable control actions. By comparing the measured performance results with the ones desired, better adjustment of the controller can be achieved to further improve the controller's performance. Computer simulation was carried out for three different cases in three traffic peaks. The results showed considerable overall improvements in the performance criteria evaluated as compared to the performance of conventional group controllers.
fuzzy logic controllers intelligence self-tuning control performance evaluation