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Advanced Control Applied to Railway and Automotive Vehicles

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  • Full or part time
    Prof T X Mei
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

About This PhD Project

Project Description

This research seeks to develop novel techniques for the control and/or condition monitoring of vehicle dynamics to either improve vehicle performance and efficiency or to provide online detection of faults and defects of key vehicle components for enhanced reliability and safety.

Control and Systems Engineering (CASE) Research at the University of Salford

Control and Systems Engineering (CASE) is part of the Engineering Research at the University of Salford that brings together a wealth of expertise that covers wide areas of advanced control and system engineering, and the core academic members of staff at the centre are internationally recognized researchers. Our philosophy for research is to seek not only theoretical advances in the related subjects, but also to explore innovative concepts and novel ideas for practical applications. Research at the centre is well funded, with support from EPSRC, TSB, DoH, MoD, Royal Society, European Commission, as well as excellent links with and direct funding from industry.

Our research excellence means that we have not only the highest calibre academics but also the first class facilities to support the leading edge research projects for both post-graduate studies and post-doctoral research.

We carry out world leading research with a particular focus on mechanical engineering challenges within the transport and railway sector. The areas of research interest include new control systems that use fault tolerant control methods, active and semi-active technologies, energy harvesting and power management, advanced condition monitoring techniques and data fusion from multiple sensors.


Candidates should have a first or upper second class honours degree in an area relevant to the subject. Candidates should have an interest in control, electrical and/or mechanical engineering as well as in transport applications. In all cases a Master’s degree or equivalent qualification or other evidence of research skills and experience is preferred but not essential.


Application where funding can be secured from other sources will be accepted at any time. For further information visit:

Further information and applying

For further information, please contact Professor TX Mei at [email protected]

For more information on research within the School of Computing Science & Engineering and to make an application please visit:

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