9 citations · 47 across the 37 of their papers we have counts for
5 papers · 1 filter
Data-driven approximation and reduction from noisy data in matrix pencil frameworks
Pauline Kergus, Ion Victor Gosea
This work aims at tackling the problem of learning surrogate models from noisy time-domain data by means of matrix pencil-based techniques, namely the Hankel and Loewner frameworks…
A framework for fitting quadratic-bilinear systems with applications to models of electrical circuits
Dimitrios S. Karachalios, Ion Victor Gosea, Athanasios C. Antoulas
In this contribution, we propose a data-driven procedure to fit quadratic-bilinear surrogate models from data. Although the dynamics characterizing the original model are strongly…
Data-driven modeling and control of large-scale dynamical systems in the Loewner framework
Ion Victor Gosea, Charles Poussot-Vassal, Athanasios C. Antoulas
In this contribution, we discuss the modeling and model reduction framework known as the Loewner framework. This is a data-driven approach, applicable to large-scale systems, which…
Reduced-order modeling of LPV systems in the Loewner framework
Ion Victor Gosea, Mihaly Petreczky, Athanasios C. Antoulas
We propose a model reduction method for LPV systems. We consider LPV state-space representations with an affine dependence on the scheduling variables. The main idea behind the pro…
On the norm and iterative model order reduction of linear switched systems
Ion Victor Gosea, Athanasios C. Antoulas
A new definition of the norm for linear switched systems is introduced. It is based on appropriately defined time-domain kernels, or equivalently, on infinite contr…