In today's technological world, physical and artificial processes are mainly described by
mathematical models, which can be used for simulation or control. These processes are …

Optimization-oriented reduced-order models should target a particular output functional,
span an applicable range of dynamic and parametric inputs, and respect the underlying …

In this article we discuss sparse matrix algorithms and parallel algorithms, as well as their
application to large-scale systems. For illustration, we solve the linear-quadratic regulator …

A mixed method is proposed which combines the factor division algorithm with the eigen
spectrum analysis for deriving reduced order models of high-order linear time invariant …

The present book is based on results of scienti? c investigations and on the materials of
special courses, o? ered for graduate and undergraduate students. The purpose of this book …

In this paper, we propose a model reduction algorithm for approximation of large-scale
linear time-invariant dynamical systems. The method is a two-sided projection combining …

We consider the solution of the balancing-related frequency-weighted model and controller
reduction problems using accuracy enhanced numerical algorithms. We propose first new …

The rapid development of MEMS‐based devices requires 3D time‐dependent simulations
for coupled physical domains (thermal, mechanical, electrical, etc.). This in turn requires the …

We describe recent developments and enhancements of the LFR-toolbox for Matlab for
building LFT-based uncertainty models and for LFT-based gain scheduling. A major …

Numerical simulation of dynamical systems have been a successful means for studying
complex physical phenomena. However, in large-scale settings, the system dimension …