Joseph McHale
- Email: pmjmc@leeds.ac.uk
- Thesis title: Crystallisation optimisation and control using surrogate modelling and adaptive model predictive control
- Supervisor: Professor Elaine Martin OBE FREng FIChemE CEng, Dr Tariq Mahmud, Keeran Ward
Profile
I am a PhD student in the Molecules to Product CDT at the University of Leeds. I gained my MEng in Chemical Engineering in 2016 from Loughborough University. I then worked as a Project and Continuous Improvement Manager for 6 years in Plastics and Food, before starting the PhD here in the Molecules to Product CDT.
Research interests
My research project is based around the application of machine learning and digital twins in controlling and optimising crystallisations. The research currently focuses on applying a hybrid of mechanistic and empirical approaches to optimally control batch cooling crystallisations. This has required automating a crystallisation setup, building population balance models, creating chemometric methods, and training predictive models using machine learning. Through applying this using model predictive control, a desired outcome such as a set supersaturation or crystal size is achieved regardless of process perturbations. Dynamic learning methods are also used to improve control based upon crystallisation response, allowing continuous improvement of the predictive model used to optimise control actions.
Qualifications
- MEng Chemical Engineering