DocumentCode :
3219182
Title :
Elevator Group Dynamic Dispatching System Based on Artificial Intelligent Theory
Author :
Cao, Liting ; Zhou, Shiru ; Yang, Shuo
Author_Institution :
Beijing Union Univ., Beijing
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
183
Lastpage :
186
Abstract :
Elevator group control is a multi-input and multi-output decision-making problem. It is very difficult to obtain high quality performance by using traditional control method due to the uncertainty of traffic flow and complexity of elevator control. A dynamic dispatching system for elevator group based on artificial intelligent technology is presented in this paper. This system includes traffic pattern identify module and dispatching control module mainly. Traffic pattern identify module based on ANN expert system is used to identify the traffic mode of elevators according to the actual traffic flow. Dispatching control module founded on ANN control theory is used to calculate dispatching parameter, the power coefficients selected according to the traffic mode, and give optimized dispatching scheme via ANN deducing. The simulation is made in MATLAB. The results show that elevator dispatching pattern is optimized, the service quality of elevator is improved, and the transportation efficiency of elevator is increased by using this control system.
Keywords :
artificial intelligence; expert systems; lifts; neural nets; traffic control; transportation; ANN expert system; MATLAB; artificial intelligence; artificial neural network; dispatching control; elevator group control; elevator group dynamic dispatching system; multiinput and multioutput decision-making; power coefficient; service quality; traffic flow; traffic pattern identify; transportation efficiency; Artificial intelligence; Control systems; Control theory; Decision making; Dispatching; Elevators; Expert systems; MATLAB; Traffic control; Uncertainty; Artificial intelligent technology; Artificial neural network; Dynamic optimized dispatching; Elevator group control; Expert system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.114
Filename :
4659468
Link To Document :
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