Research Studentship in Control Engineering
4-year D.Phil. studentship
Supervisors: Prof Kostas Margellos & Prof Mark Cannon
Model Predictive Control (MPC) is a widely used optimization-based control strategy that has proved particularly effective in engineering applications. However, significant challenges remain when applying MPC to nonlinear dynamical systems and nonconvex optimization problems, such as those encountered in neural network-based modelling.
This project aims to develop data-driven methods for constructing system models that enable the efficient solution of associated optimal control problems. The focus will be on deriving convex approximations of originally nonconvex problems, using tools such as the Koopman operator and formulations based on differences of convex functions.
A key objective is the design and analysis of predictive controllers capable of handling both parametric and unstructured uncertainties. We will adopt a scenario-based approach to represent uncertainty, which enables the derivation of rigorous performance guarantees in convex settings. The project will explore how these guarantees can be extended or interpreted in the context of the original nonconvex problems through appropriate convex reformulations.
We will apply these methods to the design of cooperative controllers for safety-critical multi-agent systems with hard constraints. Simulation studies will include decentralised control of autonomous aerial vehicles operating in restricted environments and battery management.
Eligibility
This studentship project is funded by UKRI. Due to restrictions on international student recruitment to UKRI grants, only applications from applicants who meet the residential eligibility criteria for UKRI funding will be considered. The successful applicant who is offered a place on this course will be offered a fully-funded scholarship, covering all course fees for the duration of their course and a living stipend.
Award Value
Course fees are covered at the level set for Home students c. £10,070 p.a. The stipend (tax-free maintenance grant) is c. £20,780 p.a. for the first year, and at least this amount for a further three years.
Candidate Requirements
Prospective candidates will be judged according to how well they meet the following criteria:
- A first class or strong upper second-class undergraduate honours degree in Engineering, Computer Science, Mathematics (or equivalent)
- Excellent English written and spoken communication skills
The following skills are desirable but not essential:
- Mathematical maturity
- Background in control theory and/or mathematical optimization
- Strong software skills; Experience in MATLAB/Python
Application Procedure
Informal enquiries are encouraged and should be addressed to Prof Kostas Margellos (kostas.margellos@eng.ox.ac.uk).
Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details are available on the course page of the University website.
Please quote 25ENGCO_KM in all correspondence and in your graduate application.
Application deadline: August 15, 2025
Start date: October 2025
Funded by UKRI
