Design and implementation of fuzzy based controller for modern elevator group

• Main Authors: Muhammad , Mahbubur Rashid, Alang Md Rashid, Nahrul Khair, Faruq, Alias, Rahman, Mohammed Ataur
• Format: Conference or Workshop Item
• Language: English
• Published: IEEE Explore 2011
• Subjects: TA1001 Transportation engineering (General)
• Online Access: http://irep.iium.edu.my/15084/1/Design_and_implementation_of_fuzzy_based_controller_for_modern_elevator_group.pdf; http://irep.iium.edu.my/15084/; http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6108794&tag=1

The elevator technologies are developed to serve the requested passenger’s floors with high consideration of passengers’ satisfaction and elevator optimal performance. Responding to the issue, this paper focuses on development of an elevator group controller based on fuzzy algorithm. By introducing a fuzzy controller in an elevator system, this system is developed to manage the required passenger traffic density keeping passenger waiting times within reasonable limits. To increase the performance of the elevator group three major linguistic variables are introduced within a set of fuzzy rules. These include the average waiting time (AWT), power consumption (PC), and floor traffic (FT). When the passenger traffic is high, the low fuzzy control values reduce the importance of priority of floors rather the estimated arrival time is to be minimized. The simulation was accomplished to check the priority of fuzzy system graphically while the actual prototype of elevator system is programmed by PIC device as a controller. As a result a set of fuzzy rules was drawn based on practical considerations; mainly minimization of waiting time and energy consumption. When a few hall requests are registered, the elevator controller will decide which one of the elevators will serve which of the incoming hall requests. In order to manifest the work with actual elevator service, a computer simulation of a four-cars-elevator controller in a twenty storied building is accomplished by using MATLAB™ fuzzy logic toolbox and implements the prototype experimental model of a 3 car 4 storied