About the Project
A fully funded PhD opportunity to participate in the world-leading research undertaken by the EPSRC Doctoral Landscape Award at the University of Sheffield.
Supervised by Dr J Anthony Rossiter.
The University of Sheffield is one of the leading Russell Group universities in the UK. We carry out cutting-edge research with strong links to industry. When you enrol to do a PhD with us, you will be working with world-leading academics and have access to top of the range facilities. As a PhD student you will have the opportunity to gain skills not only to conduct research, but also to take your career to the next level, whether you want to stay in academia, go into industry or the public sector, or set up your own company. You will have access to a range of training and support services to help you excel in your studies and beyond.
Project Description
Control engineering is often known as a hidden technology and yet it underpins much of the technological advances society enjoys today; autonomous driverless taxis are one easy to recognise example but a quick search will reveal that control engineering topics and ideas underpin almost every technological advance and context.
With the increasing power of computers, control engineering techniques and algorithms have also increased in their capabilities as they can exploit the computing speed and power effectively. More specifically, control is about ‘making decisions’ based on data. The faster the computer, the more data it can exploit leading to: i) more reliable decisions; ii) decisions that can be made much faster even with large amounts of data and also iii) the more nuanced the algorithm or decision making can become.
However, herein lies a risk. If the decision making/algorithm is too complicated, what happens when the scenario changes and the algorithm needs to be updated? This update process may be too expensive to do and thus, within an industrial context, the algorithm would get replaced by something with lower performance, but that is easier to maintain.
The purpose of this research is to propose approaches which bridge this gap effectively, that is, give highly insightful and robust decision making while being simple enough to facilitate cost effective maintenance and update. The specific focus will be on an area and set of techniques called model predictive control.
How to apply
Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application.
Please refer to the EPSRC DLA webpage for detailed information about the EPSRC DLA and how to apply. Applicants must ensure that they use the correct application form linked to the EPSRC DLA webpage and must submit an application for October 2027 entry. The form is unique to the EPSRC DLA. It contains the list of advertised projects from which to select, and three questions specific to the DLA.
The application deadline is 17:00 GMT 13 January 2027.
The majority of our DLA studentships will be allocated to candidates who qualify for Home fee status, in accordance with EPSRC funding regulations which place strict limits on international recruitment.
Funding Notes
The award will fund the full tuition fee and a maintenance stipend at the UKRI rate (currently £21,805 per annum) for 3.5 years, as well as a research grant to support costs associated with the pro