- Nationality: Italian
PhD Thesis
Model Predictive Control applied to turbulent flows
Supervisors
Stefano Discetti (UC3M) & Andrea Meilán Vila (UC3M, Department of Statistics)
Abstract
Controlling the behaviour of turbulent flows is of immense technological importance but their strongly nonlinear chaotic multiscale behaviour hinders the use of efficient closed-loop control techniques.
Model Predictive Control (MPC) provides a versatile framework in this field based on iterative optimization of control actions applied on compact models of the dynamics.
The goal of the research is the development of novel efficient MPC techniques for turbulent flows, which need to be highly robust to measurement noise and model uncertainty due to dynamics truncation.
PREDATOR-CM-UC3M
Grant number: 2022/070
Funding entity name: Comunidad de Madrid
Doctoral meetings 2024-2025
You can check the presentation here.
PhD in Aerospace Engineering UC3M 