Model reduction methods based on Krylov subspaces
RW Freund - Acta Numerica, 2003 - cambridge.org
In recent years, reduced-order modelling techniques based on Krylov-subspace iterations,
especially the Lanczos algorithm and the Arnoldi process, have become popular tools for …
especially the Lanczos algorithm and the Arnoldi process, have become popular tools for …
Reduced-order modeling techniques based on Krylov subspaces and their use in circuit simulation
RW Freund - Applied and Computational Control, Signals, and …, 1999 - Springer
In recent years, reduced-order modeling techniques based on Krylov-subspace iterations,
especially the Lanczos algorithm and the Arnoldi process, have become popular tools to …
especially the Lanczos algorithm and the Arnoldi process, have become popular tools to …
[图书][B] Approximation of large-scale dynamical systems
AC Antoulas - 2005 - SIAM
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 …
mathematical models, which can be used for simulation or control. These processes are …
[图书][B] A unified algebraic approach to control design
This text deals with the most fundamental deficiency of modern theory control: the lack of an
easily applicable method for the design of low order controllers. It shows that solutions to …
easily applicable method for the design of low order controllers. It shows that solutions to …
[图书][B] Krylov projection methods for model reduction
EJ Grimme - 1997 - search.proquest.com
This dissertation focuses on efficiently forming reduced-order models for large, linear
dynamic systems. Projections onto unions of Krylov subspaces lead to a class of reduced …
dynamic systems. Projections onto unions of Krylov subspaces lead to a class of reduced …
Model Reduction for Large-Scale Linear Dynamical Systems
The optimal H_2 model reduction problem is of great importance in the area of dynamical
systems and simulation. In the literature, two independent frameworks have evolved …
systems and simulation. In the literature, two independent frameworks have evolved …
Krylov subspace techniques for reduced-order modeling of large-scale dynamical systems
Z Bai - Applied numerical mathematics, 2002 - Elsevier
In recent years, a great deal of attention has been devoted to Krylov subspace techniques
for reduced-order modeling of large-scale dynamical systems. The surge of interest was …
for reduced-order modeling of large-scale dynamical systems. The surge of interest was …
[图书][B] Model reduction for control system design
G Obinata, BDO Anderson - 2012 - books.google.com
Modern methods of filter design and controller design often yield systems of very high order,
posing a problem for their implementation. Over the past two decades or so, sophisticated …
posing a problem for their implementation. Over the past two decades or so, sophisticated …
DNS-based predictive control of turbulence: an optimal benchmark for feedback algorithms
Direct numerical simulations (DNS) and optimal control theory are used in a predictive
control setting to determine controls that effectively reduce the turbulent kinetic energy and …
control setting to determine controls that effectively reduce the turbulent kinetic energy and …
[图书][B] Interpolatory methods for model reduction
Dynamical systems are at the core of computational models for a wide range of complex
phenomena and, as a consequence, the simulation of dynamical systems has become a …
phenomena and, as a consequence, the simulation of dynamical systems has become a …