DocumentCode :
2503590
Title :
Hybrid elevator group control system based on immune particle swarm hybrid optimization algorithm with full digital keypads
Author :
Luo, Fei ; Lin, Xiaolan ; Xu, Yuge ; Li, Huijuan
Author_Institution :
Dept. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
1482
Lastpage :
1487
Abstract :
Good elevator group control system would collect more information from the passengers, and make the system perform better. In this paper, a new hybrid elevator group control system with full digital keypads is proposed, on which immune particle swarm optimization (IPSO) hybrid algorithm is applied. Particle swarm optimization (PSO) algorithm has the advantages of simple model, fast convergence, and can be used in continues system. But its convergence speed would slow down lately, and will trap into local minimum easily. Artificial immune optimization(AIO) uses high cytometaplasia in optimization can avoid local minima and accelerate the optimization. After simulation under the same condition, hybrid elevator group control system with full digital keypads shows better effect than the one without digital keypads. But it still exists some disadvantages which need to be improved in the future.
Keywords :
artificial immune systems; lifts; particle swarm optimisation; artificial immune optimization; cytometaplasia; full digital keypads; hybrid elevator group control system; immune particle swarm hybrid optimization algorithm; Automatic control; Automation; Continuous time systems; Control system synthesis; Control systems; Convergence; Elevators; Particle swarm optimization; Physiology; Psychology; cellular automata; hybrid elevator group control system with full digital keypads; immune particle swarm hybrid optimization algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4594455
Filename :
4594455
Link To Document :
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