AI at Nottingham

People 

Yun He

Research Fellow - Mathematical Modelling and Optimization of Supervisor Controllers for Enhanced Energy Management in More Electric Aircraft, Faculty of Science

Contact

Biography

I am currently a post-doctoral researcher at the University of Nottingham, working with Jason Atkin on the ENGIMA project (Supervisor Control for Enhanced Electrical Energy Management).

Before that, I was a post-doctoral researcher at Institut Mine-Telecom (IMT) Atlantique in Nantes, France.

I obtained my PhD in LAAS-CNRS in Toulouse, France in 2017

Expertise Summary

I am specialized in mathematical modeling of real-life complex systems (for transport, logistics and energy management for example) and their solution using combined methods of mathematical programming and heuristics or matheuristics.

Teaching Summary

I am currently not in charge of teaching.

I used to participate in teaching activities of courses such as Algorithms and Programming, Logic, Parallel and Synchronization for undergraduate and first-year master students in University of Toulouse III Paul Sabatier. I also participated in teaching TSP lab for first-year international master students in IMT Atlantique.

Research Summary

ENIGMA Supervisor Control for Enhanced Electrical Energy Management

The ENIGMA project addresses the development of the Centralized Smart Supervisory (CSS) controller by means of formal and methodological approaches. Mathematical optimization tools has been used to obtain the formulation for the Enhanced Electrical Energy Management (E2-EM) control logics. This will ensure the ability to formally prove the correctness and optimality of the control action by construction. This strategy will provide an optimal management and sharing of available on-board electric power during overloading and failure conditions. This will pave the road towards more efficient, greener aviation.

More details

Recent Publications

Past Research

CRC ON Open Network: Continuous Time Service Network Design and Routing Problem

Inventory Routing Problem with Explicit Energy Consideration

Future Research

Complex system design and management for optimal performance.

With the development of telecommunication systems or sensor networks, the complexity of industrial systems evolves spatiotemporally. Different aspects of a system, which were spatially separated due to lack of information or communication, are now linked. Temporarily, accessibility to historical or real-time data thanks to sensors would require optimization over a much longer (several weeks or months) and much finer (in minutes or hours) time horizon.

This gives huge research opportunity to deepen theoretical insights and develop efficient solution algorithms to ensure the function and optimality of such industrial systems.

Our Address:
The University of Nottingham
University Park
Nottingham, NG7 2RD

Email us:
AI@Nottingham.ac.uk