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Adaptive controller for double-deck elevator system using genetic network programming

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4 Author(s)
Johanna Mansilla ; Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka, Japan ; Shingo Mabu ; Lu Yu ; Kotaro Hirasawa

In this paper, an improved approach is proposed based on an updating strategy using Genetic Network Programming (GNP) for the controller of Double-Deck Elevator System (DDES). Since the elevator controller has to deal with constant changes of its environment, our approach is proposed to deal with better the environment changes, resulting in a reduction of the waiting time and increasing the transportation capacity. This updating looks forward to contributing to the efficient adjustment of the system periodically according to the gained system information. The performance of the proposed method is evaluated by comparison with the conventional GNP method, which does not update the controller. By this evaluation, the enhancement of our model is confirmed.

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Date of Conference:

18-21 Aug. 2009