PhD Studentship: Enhancing UAV Manoeuvres and Control using Distributed Sensor Arrays

Supervisory Team: Dr Sergio Araujo-Estrada

Project description

We are looking for a talented and motivated PhD student to develop flight-control methods to increase manoeuvrability of Uncrewed Aerial Vehicles (UAVs).

In the last decade UAV systems have experienced significant development and by 2050, UAV-based services are estimated to create markets worth over £600 billion. These services are expected to range from delivery of goods and medical supplies to inspection and maintenance of energy infrastructure. To reach their full potential, UAV systems need to safely operate in complex environments, where external perturbations (e.g., wind gusts, obstacle avoidance, clutter environment) are difficult to sense and predict. Operating in such environments requires agile manoeuvring, however conventional controllers limit the exploitable operational envelope of these aircraft. Your PhD will address this by integrating distributed sensing and nonlinear flight control techniques.

In this project you will assess the performance of different flight control strategies using distributed sensing to achieve agile UAV manoeuvring. You’ll gain experience working with three novel technologies to enhance agile UAV manoeuvring: bio-inspired distributed sensing, machine-learning-based flight control and wind tunnel dynamic testing.

You will use an in-house bio-inspired distributed sensing system, which enables in-flight estimation of aerodynamic states and loads. You will apply machine learning to develop flight controllers that can fully exploit the information from the distributed sensing arrays. You will be able to develop and simulate the performance of your algorithms with our high-performance computing facility, Iridis. Lastly, you will utilise the R J Mitchell Wind Tunnel in combination with wind tunnel dynamic testing, to model and characterise your design, as well as test and evaluate your flights controllers under real aerodynamic conditions.

We are always looking to increase the diversity of our research teams, and we particularly encourage applications from candidates belonging to underrepresented groups.

As a PhD student at the University of Southampton you will join the Computational Engineering and Design Group (CEDG) and will work closely with Soton UAV, our world leading drone research lab, benefiting from training in the latest drone technologies.

If you wish to discuss any details of the project informally, please contact Dr Sergio Araujo-Estrada, Computational Engineering and Design Research Group, Email: S.Araujo-Estrada@soton.ac.uk, Tel: +44 (0) 2380 59 2215.

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: applications should be received no later than 30 January 2024 for standard admissions, but later applications may be considered depending on the funds remaining in place.

How To Apply

Apply online, clicking the 'Apply' button, above. Select programme type (Research), 2023/24, Faculty of Physical Sciences and Engineering, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Sergio Araujo-Estrada

 Applications should include:

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

For further information please contact: feps-pgr-apply@soton.ac.uk

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