Project Description
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 Paul Trodden and Dr Yuanbo Nie.
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
Are you fascinated by the technology that guides rockets to land precisely on floating platforms? As a rocket engine fires to change trajectory and slow the vehicle, an onboard computer must make complex decisions in real time. Because conditions can change unexpectedly due to wind, changes in equipment performance, or limitations in the mathematical model, these decisions cannot be made just once. Instead, they are repeatedly recalculated using new measurements. This approach, known as Model Predictive Control, allows a system to anticipate future behaviour, optimise its actions, and operate safely despite changing conditions.
However, current systems are often configured long before operation begins. Decisions such as how frequently calculations should be performed and how accurately they should be solved are typically fixed in advance. This can be inefficient and, in demanding situations, potentially unsafe. When conditions are changing rapidly, spending too long searching for a highly accurate solution can delay the next control decision. Conversely, when a system is operating predictably, repeatedly performing unnecessarily demanding calculations wastes valuable computing power and energy.
In collaboration with Airbus Defence and Space Limited, this project will develop new optimisation algorithms that can adapt automatically to the uncertainty experienced by a system. The research will investigate how to balance computation speed, accuracy, and optimality in real time. When conditions are highly uncertain, the system will prioritise fast decisions to maintain rapid feedback. When the system is well understood and operating predictably, it will invest more computational effort in finding higher-quality solutions.
A key challenge is that many important sources of uncertainty cannot be measured directly. These may include changes in system parameters, equipment behaviour that differs from its mathematical model, or physical effects that have not been captured. You will therefore develop methods to estimate and quantify these uncertainties, including their likelihood and potential impact on system behaviour. This information will then be used to automatically determine how demanding each optimisation calculation needs to be, and what level of performance can be safely guaranteed.
Building on the optimisation and estimation schemes, the project will establish a new adaptive control framework in which uncertainty, optimisation, and decision-making continuously inform one another. Rather than using a fixed computational strategy, the system will decide how much computational effort is appropriate for the conditions it currently faces, while ensuring that its decisions remain feasible and the system remains stable. The framework will therefore allow computational effort to adapt without compromising these essential safety requirements
The research has potential applications across safety-critical autonomous systems, including spacecraft landing, hybrid-electric aircraft, and urban air mobility. By enabling autonomous systems to adapt their computational behaviour as conditions change, this work could help make future technologies more reliable, efficient, and capable of operating safely in uncertain real-world environments.
This studentship is part of an interdisciplinary research community at the University of Sheffield, bringing together expertise in control engineering, computational mathematics, and aerospace systems. You will work alongside leading researchers and benefit from links with industrial partners, gaining insight into real-world engineering challenges and opportunities for collaboration. Comprehensive training in research skills, project management, communication, and career development will support you throughout your PhD, alongside opportunities to attend international conferences, undertake public engagement, and develop external collaborations.
Funding Information
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 project.
Eligibility Requirements
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.
Application Process
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.
