Title:

Time-domain data-driven model reduction

Abstract:

Moment matching is one of the possible approaches for reducing the order of a system, obtaining a so-called reduced order model. Traditionally, moment matching consists in the problem of interpolating points in the complex plane. The approach can also be reformulated as a method in which steady-state signals, instead of points, are interpolated. From this point of view, new results and ideas arose both inside and outside the model reduction literature. The seminar focuses on data-driven model reduction, a problem which lies between the domains of model reduction and system identification.

Biography:

Giordano Scarciotti is a Senior Lecturer at Imperial College London. He received his B.Sc. and M.Sc. degrees in Automation Engineering from the University of Rome “Tor Vergata”, Italy, in 2010 and 2012, respectively. In 2012 he joined the Control and Power Group, Imperial College London, UK, where he obtained a Ph.D. degree in 2016 with a thesis on approximation, analysis and control of large-scale systems. He also received an M.Sc. in Applied Mathematics from Imperial College in 2020. His current research interests are focused on analysis and control of uncertain systems, model reduction and optimal control. He was a visiting scholar at New York University in 2015 and at University of California Santa Barbara in 2016 and he is currently a Visiting Fellow of Shanghai University. He is the recipient of an Imperial College Junior Research Fellowship (2016), of the IET Control & Automation PhD Award (2016), the Eryl Cadwaladr Davies Prize (2017) and an ItalyMadeMe award (2017). He is a Senior Member of IEEE, a member of the IEEE CSS Conference Editorial Board, of the IFAC and IEEE CSS Technical Committees on Nonlinear Control Systems and has served in the International Programme Committees of multiple conferences. He is the National Organising Committee Chair for the EUCA European Control Conference 2022 and the Invited Session Chair for IFAC Symposium on Nonlinear Control Systems 2022.

 

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