Reducing the size and emissions of gas turbine engines used in the aeronautics industry forces manufacturers to explore new operating conditions. An undesirable phenomenon called thermo-acoustic instabilities may occur, caused by the coupling between combustion dynamics and the acoustics of the combustion chamber. To help predict, detect and suppress it, we explore various approaches. We will discuss the design of observers for infinite-dimensional systems, Fourier-based reduced-order modeling as well as a Machine-Learning approach based on high-fidelity simulation data.
Biography: Florent Di Meglio is Associate Professor at the Centre Automatique et Systèmes of MINES ParisTech, PSL Research University. He received his Ph.D. from the same university in Mathematics and Control in 2011, and was a Posdoctoral Researcher at UC San Diego from 2011 to 2012. His current research interests include control and estimation design for PDEs, with applications in process control, and for exoskeletons.