Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504067
Title: Intelligent model-based robust control for tilting railway vehicles
Author: Zamzuri, Hairi
ISNI:       0000 0004 2675 0408
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2008
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Abstract:
High-speed trains have become one of the main means of public transportation around the world. The use of tilting train technologies on high-speed trains has contributed to cost effectiveness by reducing journey time between two places without the need to develop a new high-speed rail track infrastructure. Current technologies in tilting railway vehicles use a 'precedence' control scheme. This scheme uses a measurement from the front vehicle to capture 'precedence' information. Research on local sensor loop control strategies is still important to overcome the complexity of using precedence control technique. Work using conventional and modern control approaches has been investigated by previous researches. This study further extends these by investigating a particular intelligent control technique using fuzzy logic in designing the local feedback tilt control scheme.
Supervisor: Not available Sponsor: Universiti Teknologi Malaysia (Johor Bahru, Malaysia)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.504067  DOI: Not available
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