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- model reduction (3)
- balanced truncation (2)
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- matrix pencils (1)
- matrix sign function (1)
- moment matching (1)
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Descriptor systems present a general
mathematical framework for the modelling, simulation and control of complex dynamical systems arising in many areas of mechanical,
electrical and chemical engineering. This
paper presents a survey of the current theory of descriptor systems,concerning
solvability, stability, model reduction, controllability, observability and optimal control.
In this paper we consider the rational interpolation problem consisting in finding a rational matrix-valued function that
interpolates a given set of parameters. We briefly describe two different numerical methods for solving this problem. These are
the vector fitting and the frequency domain subspace identification method. Several numerical examples are given that compare
the properties of these methods. Furthermore, we discuss the computation of a (minimal) state space realization of a rational
function. Model order reduction methods such as modal approximation and balanced truncation are also presented. These
methods can be used to compute a reduced-order approximation of the realized dynamical system.
In this paper we consider structure-preserving model reduction of
second-order systems using a~ba\-lan\-ced truncation approach.
Several sets of singular values are introduced for such systems,
which lead to different concepts of balancing and different
second-order balanced truncation methods. We compare the
properties of these methods on numerical examples.
Passivation of LTI systems
(2007)
In this paper we consider a passivation procedure for linear time-invariant systems.
This procedure is based on the spectral properties of related Hamiltonian matrices.
We also present a structure-preserving algorithm for computing the imaginary
eigenvalues and the corresponding eigenvectors of Hamiltonian matrices.
Numerical examples are given.
In this paper we give an overview of model
order reduction techniques for coupled
systems. We consider linear time-invariant
control systems that are coupled through
input-output relations and discuss model
reduction of such systems using moment
matching and balanced truncation.
Structure-preserving approaches to model
order reduction of coupled systems are also
presented. Numerical examples are given.
In this paper we discuss the numerical
solution of projected generalized Lyapunov
equations using the matrix sign function
method. Such equations arise in stability
analysis and control problems for
descriptor systems including model reduction
based on balanced truncation. It is known
that the matrix sign function method applied
to a matrix pencil $\lambda E-A$ converges
if and only if $\lambda E-A$ is of index at
most two. The convergence is quadratic if
$E$ is nonsingular, and it is linear,
otherwise. We will propose a modification
of the matrix sign function method that
converges quadratically for pencils of
arbitrary index. Numerical examples will be
presented to demonstrate the properties of
the modified method.
We consider the numerical solution of projected Lyapunov equations using Krylov subspace iterative methods. Such equations
play a fundamental role in balanced truncation model reduction of descriptor systems. We present generalizations of
the extended block and global Arnoldi methods to projected Lyapunov equations and compare these methods with the alternating direction implicit method with respect to performance on different examples.
A deflation strategy is also proposed to overcome possible breakdown in the
recurrence.
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 basis concepts from linear system theory and then
present balanced truncation model reduction methods for descriptor systems and
discuss their algorithmic aspects. The efficiency of these methods is demonstrated
by numerical experiments.
We generalize an alternating direction implicit method and the Smith method for
large-scale projected generalized Lyapunov equations. Such equations arise in model reduction for
descriptor systems. Low rank versions of these methods are also presented, that can be used to
compute low rank approximations to the solution of projected generalized Lyapunov equations with
low rank symmetric, positive semidefinite right-hand side. Numerical examples are presented.
In this paper we discuss the stability and model order reduction of coupled linear
time-invariant systems. Sufficient conditions for a closed-loop system to be asymptotically stable are
given. We present a model reduction approach for coupled systems based on reducing the order of the
subsystems and coupling the reduced-order subsystems by the same interconnection matrices as for
the original model. Such an approach allows to obtain error bounds for the reduced-order closed-loop
system in terms of the errors in the reduced-order subsystems. Model reduction of coupled systems
with unstable subsystems is also considered. Numerical examples are given.