In the past decades, Model Order Reduction (MOR) has demonstrated its robustness and
wide applicability for simulating large-scale mathematical models in engineering and the …

The past few decades have seen a significant spurt in developing lower-order, parsimonious
models of large-scale dynamical systems used for design and control. These surrogate …

The simulation and control of complex technical systems in many fields of application, like
structural mechanics, electrothermics, or acoustics, requires methods for the efficient …

The frequency response of vibro-acoustic systems can be improved by using various forms
of damping materials. Their material properties are typically varying with the excitation …

This is a survey of model order reduction (MOR) methods based on momentmatching.
Moment-matching methods for linear non-parametric and parametric systems are reviewed …

We propose a posteriori error bounds for reduced-order models of non-parametrized linear
time invariant (LTI) systems and parametrized LTI systems. The error bounds estimate the …

A fully adaptive model order reduction scheme based on moment matching is proposed to
derive the reduced-order models of linear time-invariant (LTI) systems. According to the …

The model order reduction of second-order dynamical multi-input and multi-output (MIMO)
systems with proportional damping arising in the numerical simulation of mechanical …

In this paper, we address discrete linear systems in the frequency domain, where both
frequency and random parameters are considered. Sampling such a system many times is …

We provide a publicly available collection of sixteen large-scale benchmark nonlinear state-
space models in this contribution. The models are written in the MATLAB language and are …