Optimised intelligent tilt controller scheme using genetic algorithms

This paper presents work on a fuzzy control design for improving the performance of tilting trains with local-per vehicle control, i.e. without employing precedence control.An optimisation procedure using Genetic Algorithms as employed to determine both the best fuzzy output membership function and...

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Bibliographic Details
Main Authors: Zamzuri, Hairi, Zolotas, Argyrios, Goodall, Roger
Format: Conference or Workshop Item
Language:English
Published: 2006
Subjects:
Online Access:http://eprints.utm.my/5473/
http://eprints.utm.my/5473/1/HairiZamzuri2006_Optimisedintelligenttiltcontrollerscheme.pdf
Description
Summary:This paper presents work on a fuzzy control design for improving the performance of tilting trains with local-per vehicle control, i.e. without employing precedence control.An optimisation procedure using Genetic Algorithms as employed to determine both the best fuzzy output membership function and best PID controller parameters. The objective function for the GA procedure was based on a performance index combining the system response on curved and straight track. Simulation results illustrate the effectiveness of the scheme compared to the conventional nulling-tilt approach.