  In this paper, we present a data-driven approach to identify second-order
systems, having internal Rayleigh damping. This means that the damping matrix
is given as a linear combination of the mass and stiffness matrices. These
systems typically appear when performing various engineering studies, e.g.,
vibrational and structural analysis. In an experimental setup, the frequency
response of a system can be measured via various approaches, for instance, by
measuring the vibrations using an accelerometer. As a consequence, given
frequency samples, the identification of the underlying system relies on
rational approximation. To that aim, we propose an identification of the
corresponding second-order system, extending the Loewner framework for this
class of systems. The efficiency of the proposed method is demonstrated by
means of various numerical benchmarks.

Optimization and Control;Numerical Analysis;Systems and Control;Systems and Control;Numerical Analysis