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  Model Predictive Control for Autonomous Vehicles and Robots [Self Funded Students Only]

   Cardiff School of Computer Science & Informatics

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  Dr Kirill Sidorov  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Model predictive control (MPC) is a family of modern control methods that have demonstrated impressive performance in a variety of scenarios, including in robotics and autonomous vehicle control. Such methods rely on models that can predict a system's future behaviour in response to control inputs in order to find the optimal actions that drive the system to a desired state. MPC methods can handle highly non-linear systems, with complex interactions between inputs and outputs.

While MPC is now an established field, a number of questions remain open. This project aims to further enrich this family of methods by using state-of-the-art machine learning techniques to improve predictive modelling. In particular, one or more of the following topics will be investigated:

(1) Effective techniques for on-line learning of predictive models from sparse training data.

(2) Explicit modelling of uncertainties in the predictive models.

(3) Multi-modal and multi-objective control optimisation.

(4) Modelling interactions with potentially dynamic environment.

The candidate will be working within an expert team at the forefront of modern control theory and state-of-the-art machine learning. This project will thus equip the student with specialist knowledge in advanced computer science, focusing on transferable skills in machine learning (especially deep learning), data mining, and high-performance numerical computing.

The prospective candidate will perform both theoretical research and carry out experimental work (in simulations and potentially with autonomous vehicle prototypes). Thus, an interest and practical experience in electronics and robotics will be a bonus.

Keywords: machine learning, control theory, robotics

Contact for information on the project: [Email Address Removed]

Academic criteria:  

A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject.  Applicants with appropriate professional experience are also considered. Degree-level mathematics (or equivalent) is required for research in some project areas. 

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component. 

This application is open to students worldwide. 

How to apply

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below 

This project is accepting applications all year round, for self-funded candidates via  

In order to be considered candidates must submit the following information:  

  • Supporting statement  
  • CV  
  • In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD 
  • Qualification certificates and Transcripts 
  • Proof of Funding. For example, a letter of intent from your sponsor or confirmation of self-funded status (In the funding field of your application, insert Self-Funded) 
  • References x 2  
  • Proof of English language (if applicable) 

If you have any questions or need more information, please contact [Email Address Removed] 

Computer Science (8)

Funding Notes

This project is offered for self-funded students only, or those with their own sponsorship or scholarship award.

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