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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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
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author Zamzuri, Hairi
Zolotas, Argyrios
Goodall, Roger
author_facet Zamzuri, Hairi
Zolotas, Argyrios
Goodall, Roger
author_sort Zamzuri, Hairi
building UTeM Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T20:51:58Z
format Conference or Workshop Item
id utm-5473
institution Universiti Teknologi Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T20:51:58Z
publishDate 2006
recordtype eprints
repository_type Digital Repository
spelling utm-54732017-08-28T08:43:10Z http://eprints.utm.my/5473/ Optimised intelligent tilt controller scheme using genetic algorithms Zamzuri, Hairi Zolotas, Argyrios Goodall, Roger TK Electrical engineering. Electronics Nuclear engineering TF Railroad engineering and operation 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. 2006-08-30 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/5473/1/HairiZamzuri2006_Optimisedintelligenttiltcontrollerscheme.pdf Zamzuri, Hairi and Zolotas, Argyrios and Goodall, Roger (2006) Optimised intelligent tilt controller scheme using genetic algorithms. In: UKACC International Control Conference, 30 Sept. - 1 Oct. 2006, Glasgow, UK. http://ukacc.group.shef.ac.uk/proceedings/control2006/icc2006.htm
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
TF Railroad engineering and operation
Zamzuri, Hairi
Zolotas, Argyrios
Goodall, Roger
Optimised intelligent tilt controller scheme using genetic algorithms
title Optimised intelligent tilt controller scheme using genetic algorithms
title_full Optimised intelligent tilt controller scheme using genetic algorithms
title_fullStr Optimised intelligent tilt controller scheme using genetic algorithms
title_full_unstemmed Optimised intelligent tilt controller scheme using genetic algorithms
title_short Optimised intelligent tilt controller scheme using genetic algorithms
title_sort optimised intelligent tilt controller scheme using genetic algorithms
topic TK Electrical engineering. Electronics Nuclear engineering
TF Railroad engineering and operation
url http://eprints.utm.my/5473/
http://eprints.utm.my/5473/
http://eprints.utm.my/5473/1/HairiZamzuri2006_Optimisedintelligenttiltcontrollerscheme.pdf