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Publisher: Canadian Center of Science and Education
Languages: English
Types: Article
Subjects:
The design and simulation of a four-cars-elevator controller in a nine storey building is described in this paper. The design and simulation were accomplished using MATLABTM fuzzy logic toolbox. The logic of the controller of a multi-car elevator has to be designed in such a way that the average waiting time is minimized while keeping the energy consumption of the system optimum. This is a multi-criteria optimization problem in stochastic environment and is best approached through Artificial Intelligent techniques. The work here focuses mainly on extracting the rules to minimize factors (i.e. waiting time, travelled distance and riding time) in order to minimize the energy consumed by the system. In this paper a detailed algorithm is presented to achieve the multiple objectives of minimizing the waiting time and the distance travelled simultaneously. This was accomplished by distributing different weightage to different quantities and then minimizing a combined cost. A simulator has been built with interactive GUI in Matlab to evaluate the efficacy of the algorithm.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Crites, R. & Barto, A. (1998). Elevator group control using multiple reinforcement learning agents. Machine Learning: 33, 235-262.
    • Kim, C. Kyoung, A., Kwang, H.L., and Kim, J.o. (1998). Design and Implementation of a Fuzzy Elevator Group Control System. IEEE Transactions on Systems. Man and Cybernetics, Part A: Systems and Humans: 28, 277-287.
    • Koehler, J. & Ottiger, D. (2002). An AI-based approach to destination control in elevators. AI Magazine: 23(3), 59-79.
    • Marja-Liisa, S. M. (1997). Elevator Group Control with Artificial Intelligenceā€, KONE Corporation, Helsinki University of Technology, Systems Analysis, Laboratory, Research Reports, A67, October 1997.
    • Tan K.K. Marzuki K., & Rubiyah Y. (1997). Intelligent Elevator Control By Ordinal Structure Fuzzy Logic Algorithm: Proc. of ICARCV 97, Singapore.
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