Please use this identifier to cite or link to this item: https://doi.org/10.1049/ip-epa:20000329
Title: Differential evolution based tuning of fuzzy automatic train operation for mass rapid transit system
Authors: Chang, C.S. 
Xu, D.Y.
Issue Date: 2000
Source: Chang, C.S., Xu, D.Y. (2000). Differential evolution based tuning of fuzzy automatic train operation for mass rapid transit system. IEE Proceedings: Electric Power Applications 147 (3) : 206-211. ScholarBank@NUS Repository. https://doi.org/10.1049/ip-epa:20000329
Abstract: Train performance of mass rapid transit systems can be improved with the use of fuzzy controllers in automatic train operation (ATO) systems. The tuning of these fuzzy controllers is presented using the algorithm of differential evolution (DE). The basic DE algorithm is modified to optimise a multiobjective function comprising punctuality, riding comfort and energy usage. Using this algorithm, the fuzzy ATO controller is tuned for each interstation train run. In operation, the controller adjusts each train's control according to the current operating conditions. A fuzzy ATO controller model was previously developed by the authors and is used to demonstrate the effectiveness of the tuning scheme. © IEE, 2000.
Source Title: IEE Proceedings: Electric Power Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/62039
ISSN: 13502352
DOI: 10.1049/ip-epa:20000329
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

72
checked on Dec 14, 2017

WEB OF SCIENCETM
Citations

43
checked on Nov 17, 2017

Page view(s)

20
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.