Advanced control strategies for tilting trains

Zolotas, Argyrios (2002) Advanced control strategies for tilting trains. Doctoral thesis (PhD), Loughborough University.

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The use of tilting bodies on railway vehicles is becoming increasingly widespread: a number of well-established services using tilt technology already exist around the world, and will appear again in the UK over the next year or so. The motivation for tilting railway vehicles is that they give a cost-effective means of achieving a substantial reduction in journey time by increasing the vehicle speed during curves. Early tilt controller designs were based upon local vehicle measurements, however at that time this approach did not prove very successful. Nowadays most European manufacturers use the so called ‘precedence’ control scheme, utilising measurements from precedent vehicles to achieve ‘precedence’ information. However, achieving a satisfactory local tilt control strategy is still an important research target because of the system simplifications and more straightforward failure detection. The thesis describes a comprehensive study of tilt control, and its aim is to employ advanced control techniques - based upon practical sensors - with the particular objective of identifying effective strategies which can be applied to each vehicle independently, i.e. without using precedence control. The sensors employed for control design are in particular mounted on the vehicle passenger coach. Most of the work has been undertaken using Matlab, and this has included a proper assessment of the ride quality issues.

Item Type: Thesis (Doctoral)
Keywords: Control; Tilting trains; High Speed Rail Vehicles
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: T Technology
T Technology > TA Engineering (General). Civil engineering (General) > TA0174 Engineering design
T Technology > TJ Mechanical engineering and machinery > TJ0212 Control engineering systems. Automatic machinery (General)
Depositing User: Argyrios Zolotas
Date Deposited: 23 Nov 2012 09:22
Last Modified: 13 Dec 2018 14:20
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