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 …

Robustness is often of crucial importance in control system design. Real engineering
systems are vulnerable to external disturbance and measurement noise and there are …

This paper summarises the model reduction techniques used for the reduction of large-scale
linear and nonlinear dynamic models, described by the differential and algebraic equations …

The FEniCS Project set out in 2003 with an idea to automate the solution of mathematical
models based on differential equations. Initially, the FEniCS Project consisted of two …

In this paper we present the cyclic low-rank Smith method, which is an iterative method for
the computation of low-rank approximations to the solution of large, sparse, stable Lyapunov …

This paper presents the Cholesky factor--alternating direction implicit (CF--ADI) algorithm,
which generates a low rank approximation to the solution X of the Lyapunov equation AX+ …

We discuss the relation of a certain type of generalized Lyapunov equations to Gramians of
stochastic and bilinear systems together with the corresponding energy functionals. While …

In this paper we give a survey on balanced truncation model order reduction for linear time-
invariant continuous-time systems in descriptor form. We first give a brief overview of the …

The author proposes a novel algorithm with enhanced numerical robustness for computing
singular perturbation approximations of linear, continuous or discrete systems. This …

Three algorithms for the model reduction of large-scale, continuous-time, time-invariant,
linear, dynamical systems with a sparse or structured transition matrix and a small number of …