A New Real Time Control Approach for Time Efficiency in Group Elevator Control System

Abstract

In parallel with the increase seen in the number of high-rise buildings, vertical transport systems are progressing. One of the results of this progress is the emergence of group elevator systems and their primary aim is to transport its passengers to the target floor the fastest way possible. Studies on this field are generally simulation and optimization based and they have an aim of minimizing the passengers’ waiting and traveling periods. In this study, a real time group elevator experimental setup was created and an optimization algorithm was applied on the setup. Genetic algorithm was chosen as optimization algorithm and this method was tested in an elevator prototype of 10 floors and 5 cabins. The results obtained revealed efficiency, performance and accuracy of proposed method.

Keywords

• group elevator systems,optimization,genetic algorithm,average waiting time,real time control

Kaynakça

1. [1] Fernandez J. R. and Cortes P. A Survey of Elevator Group Control Systems for Vertical Transportation: A Look at Recent Literature, IEEE Control Systems, Vol. 35, No. 4, 2015, pp. 38-55.
2. [2] Fernandez J., Cortes P., Munuzuri J. and Guadix J. Dynamic Fuzzy Logic Elevator Group Control System With Relative Waiting Time Consideration, IEEE Transactions on Industrial Electronics, Vol. 61, No. 9, 2014, pp. 4912-4919.
3. [3] Jamaludin J., Rahim N. A. and Hew W. P. An elevator group control system with a self-tuning fuzzy logic group controller, IEEE Transactions on Industrial Electronics, Vol. 57, No. 12, 2010, pp. 4188–4198.
4. [4] Valdivielso A. and Miyamoto T. Multicar-Elevator group control algorithm for interference prevention and optimal call allocation, IEEE Transactions on Systems, Man and Cybernetics Part A: Systems and Humans, Vol. 41, No. 2, 2011, pp. 311-322.
5. [5] Utgoff P. E. and Connell M. E. Real-time combinatorial optimization for elevator group dispatching, IEEE Transactions on Systems, Man, and Cybernetics A, Vol. 42, No. 1, 2012, pp. 130–146.
6. [6] Sun J. Zha Q. C. and Luh P. B. Optimization of group elevator scheduling with advance information, IEEE Transactions on Automation Science and Engineering, Vol. 7, No. 2, 2010, pp. 352–363.
7. [7] Bolat B. and Cortés P. Genetic and tabu search approaches for optimizing the hall call—car allocation problem in elevator group systems, Applied Soft Computing, Vol. 11, No. 2, 2011, pp. 1792–1800.
8. [8] Tartan E. O., Erdem H. and Berkol A. Optimization of waiting and journey time in group elevator system using genetic algorithm, IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings, pp. 361-367, Jun. 2014, Alberobello.

9. [9] Fei L., Xiaocui Z. and Yuge X. A new hybrid elevator group control system scheduling strategy based on Particle Swarm Simulated Annealing Optimization algorithm, 8th World Congress on Intelligent Control and Automation (WCICA), pp. 5121-5124, Jul. 2010, Jinan.
10. [10] Baygin M. and Karakose M. A New Intelligent Group Elevator Control Approach, in Proceedings of the 15th International Symposium (MECHATRONIKA), pp. 1–6, Dec. 2012, Prague.
11. [11] Yuge X., Fei L. and Xiaolan L. Hybrid destination registration elevator group control system with artificial immune optimization algorithm, 8th World Congress on Intelligent Control and Automation (WCICA), pp. 5067-5071, Jul. 2010, Jinan.
12. [12] Munoz D. M., Lianos C. H., Rincon M. A. and Van Els R. H. Distributed approach to group control of elevator systems using fuzzy logic and FPGA implementation of dispatching algorithms, Engineering Applications of Artificial Intelligence, Vol. 21, No. 8, 2008, pp. 1309-1320.
13. [13] Yu L., Zhou J., Mabu S., Hirasawa K. and Hu J. A Double-deck Elevator Group Supervisory Control System with Destination Floor Guidance System using Genetic Network Programming, SICE-ICASE International Joint Conference, pp. 5989-5994, Oct. 2006, Busan.
14. [14] Baygin M. and Karakose M. Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving, The Scientific World Journal, Vol. 2013, 2013, pp. 1-12.
15. [15] Karakose M., Baygin M. and Baygin N. An analysis approach for optimization based reconfiguration in photovoltaic arrays, IEEE 23rd International Symposium on Industrial Electronics (ISIE), pp. 954-959, Jun. 2014, Istanbul.
16. [16] Yetis H., Baygin M. and Karakose M. A New Micro Genetic Algorithm Based Image Stitching Approach in Camera Arrays, The 5th International Conference on Manufacturing Engineering and Process (ICMEP), May. 2016, Istanbul.