DocumentCode :
1428825
Title :
Combined heuristic knowledge and limited measurement based fuzzy logic antiskid control for railway applications
Author :
Cheok, Adrian David ; Shiomi, Shogo
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Volume :
30
Issue :
4
fYear :
2000
fDate :
11/1/2000 12:00:00 AM
Firstpage :
557
Lastpage :
568
Abstract :
In modern railway applications, the prevention of wheel skid is very important. This is because wheel skid can lead to an increase in noise and vibration from wheels with flat points, as well as an increased braking distance. However, conventional antiskid control has problems because the train wheel adhesion and skid characteristics are difficult and time consuming to accurately model. In addition, adequate measured numerical data describing wheel skid is difficult and expensive to obtain from actual railway systems. Therefore, a fuzzy logic based antiskid controller was implemented, where both linguistic and numerical system information could be used. In this paper, the design and implementation of the fuzzy logic controller is described. Results show that the antiskid controller has a very good performance, and performs better than a conventional controller. The described controller is currently running in Mitsubishi Electric railway brake sets in both Japan and overseas
Keywords :
braking; friction; fuzzy control; fuzzy logic; fuzzy neural nets; heuristic programming; railways; Mitsubishi Electric railway brake sets; fuzzy logic antiskid control; heuristic knowledge; limited measurement; noise; railway applications; skid characteristics; train wheel adhesion; vibration; wheel skid; Acoustic noise; Adhesives; Control systems; Fuzzy logic; Fuzzy systems; Mathematical model; Process control; Rail transportation; Training data; Wheels;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/5326.897082
Filename :
897082
Link To Document :
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