PhD Studentship - CBF Control for Safety-Critical Multi-Agent Autonomous Systems

Application deadline: All year round

Research theme: Control systems and theory, Applied Mathematics

How to apply: uom.link/pgr-apply-2425

Number of positions: 1

Open to: UK

This 3.5 year project is fully funded for home students; the successful candidate will receive an annual tax free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year.

Modern applications—from power grids to vehicle platoons—depend on large networks of autonomous subsystems. Without a solid theoretical underpinning, ensuring both collective objectives (coordination) and safety constraints can be intractable. Your work will bridge this gap by providing generalizable, provable design approach that apply across a wide range of networked systems.

This 3.5-year PhD project will develop a rigorous theoretical framework to ensure both coordinated behaviour and safety in interconnected dynamical systems. You will design and analyse a two-layer control architecture:

Coordination Layer:

Formulate passivity-based conditions that guarantee agents—modelled as general nonlinear systems—synchronize their outputs or follow desired collective patterns purely through local interactions.

Safety Layer:

Introduce a supervisory “filter” based on control-barrier functions that provably enforces state constraints (e.g. collision avoidance, bounded inputs) without destroying the coordination guarantees.

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.

Candidate Profile:

We seek someone with strong mathematical maturity in control theory, dynamical systems, or applied mathematics. Familiarity with nonlinear systems analysis, graph theory, and formal methods (e.g., barrier certificates) is advantageous. You will collaborate with experts in control theory and have opportunities to test theoretical insights in simulation and hardware environments.

To apply please contact the main supervisor, Dr. Lanlan Su - lanlan.su@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

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