This work presents a nonintrusive physics-preserving method to learn reduced-order models
(ROMs) of Lagrangian systems, which includes nonlinear wave equations. Existing intrusive …

In order to apply control theory in small autonomous vehicles, mathematical models with
small numbers of states are required for using the limited computational power in embedded …

In this thesis, structure-preserving model order reduction for dynamical systems is studied.
The particular focus lies on mechanical systems described by differential equations with …

Considering the use of dynamical systems in practical applications, often only limited
regions in the time or frequency domain are of interest. Therefore, it usually pays off to …

Model order reduction (MOR) methods that are designed to preserve structural features of a
given full order model (FOM) often suffer from a lower accuracy when compared to their non …

This paper compares the computational performances of four model order reduction
methods applied to large-scale electric power RLC networks transfer functions with many …

The method known as the dominant pole algorithm (DPA) has previously been successfully
used in combination with model order reduction techniques to approximate standard linear …

In this paper, we propose an improved method for computing the H_∞ norm of linear
dynamical systems that results in a code that is often several times faster than existing …

This chapter offers an introduction to Model Order Reduction (MOR). It gives an overview on
the methods that are mostly used. It also describes the main concepts behind the methods …

We consider the problem of determining an optimal semi‐active damping of vibrating
systems. For this damping optimization we use a minimization criterion based on the …