PhD Studentship – Enhancing Adaptive Control System Performance using Advanced Machine Learning Techniques

at University of Hertfordshire
Published August 23, 2023
Location Hatfield, United Kingdom
Category Machine Learning  
Job Type Scholarship  



  • Qualification type: PhD
  • Subject area: Control and Machine Learning
  • Location/Campus: College Lane, Hatfield
  • Start date: October 2023 or as soon as possible thereafter
  • Closing application date: 4 September 2023
  • Duration: three years, full time

Funding information (fully funded for UK, EU and international students)

Annual tax-free bursary of approximately £18,622 pa, plus tuition fees (£5590 for UK or £14,905 for International and EU applicants).

Project Details

In recent years, there has been a significant progress in the application of Machine Learning (ML) across various domains. Emerging techniques such as DDPG (Deep Deterministic Policy Gradient), PPO (Proximal Policy Optimisation), and TD3 (Twin Delayed DDPG) have shown promising performance in dealing with control systems. However, the performance and robustness of these algorithms are still undergoing investigation, and their generalisability compared to conventional adaptive and robust controllers remains not fully comprehended.

This project aims to comprehensively analyse the performance and robustness of state-of-the-art ML techniques on control system problems. It will extract both the limitations and advantages of these algorithms. Moreover, the project will develop novel ML solutions that not only push performance boundaries but also exhibit superior generalisability compared to traditional adaptive control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong foundation in mathematical and control theory is essential for conducting this research.

The applicant should have a relevant degree, ideally with a background (or strong interest in developing knowledge) in the following areas:

- Control theory (classical, adaptive, and optimal controllers).

- Machine learning theory and techniques.

- Nonlinear stability and statistical analysis.

- Programming skills in Matlab, Python, or other relevant tools.

Entry requirements

Applications are invited from individuals with a first or upper second-class degree (or equivalent) in a relevant discipline such as, engineering, maths, computer science, etc. A master’s degree is essential. We are seeking applicants with very good analytical and programming skills. In some areas priority will be given to applicants with demonstrable practical engineering skills and experimental experience.


The studentship is open to UK/EU and international applicants.

How to Apply

Informal enquires can be made to Dr Pouria Sarhadi, the project supervisor, or Prof. Pandelis Kourtessis, Associate Dean Research and Enterprise.

Please download and complete an application form

In section 11 you must provide a comprehensive personal statement of up to 500 words describing your motivation to do research on this project at the University of Hertfordshire.

Please also send with your application form:

  • A research proposal not exceeding 2 pages
  • Two academic references
  • Copies of qualification certificates and transcripts
  • Certification of English language competence (minimum IELTS 6.5 or equivalent) for candidates for whom English is not their first language.

Your completed application should be emailed to the Doctoral College via the ‘Apply’ button above

Interview dates: week beginning 11 September 2023

Expected studentship start date: 1 October 2023

Location: University of Hertfordshire, College Lane Campus, AL10 0ST