DocumentCode :
3485263
Title :
Elevator group control system tuned by a fuzzy neural network applied method
Author :
Imasaki, Naoki ; Kubo, Susumu ; Nakai, Shoji ; Yoshitsugu, Tatsuo ; Kiji, Jun-Ichi ; Endo, Tsunekazu
Author_Institution :
Syst. & Software Eng. Lab., Toshiba Corp., Kawasaki, Japan
Volume :
4
fYear :
1995
fDate :
20-24 Mar 1995
Firstpage :
1735
Abstract :
We have developed a high-performance elevator group control system with a performance tuning function, which employs a fuzzy neural network as a performance forecasting model of the elevator system. The fuzzy neural network, which is a structured neural network based on a fuzzy reasoning framework, stores the correlation between control-parameters and the response of the elevator group as a fuzzy rule set. It performs a fuzzy rule-based reasoning to forecast the system performance of the elevator group. The performance tuning function utilizes the forecasting model in order to search the optimal control parameters which give the best system performance in the present traffic situation. The fuzzy neural network applied system can automatically adapt itself to various traffic situations. This paper gives the overview of the elevator group control system with the fuzzy neural network and shows the validity of the methodology by some simulation results
Keywords :
adaptive control; fuzzy control; fuzzy neural nets; inference mechanisms; intelligent control; knowledge based systems; lifts; optimal control; adaptive control; elevator group control system; fuzzy neural network; fuzzy rule set; fuzzy rule-based reasoning; optimal control; performance forecasting model; performance tuning function; Communication system traffic control; Control system synthesis; Control systems; Elevators; Fuzzy control; Fuzzy neural networks; Fuzzy reasoning; Predictive models; System performance; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
Type :
conf
DOI :
10.1109/FUZZY.1995.409916
Filename :
409916
Link To Document :
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