Balanced Truncation Model Reduction for Large-Scale Systems in Descriptor Form
By Volker Mehrmann, Tatjana Stykel. 2005
227 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Numerical Analysis, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/513112ae80e489ca9c45df89102ddfbf5013e363
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
In Numerical Analysis
- Patrick Kürschner
- Peter Benner
- Jens Saak
- Bernd Simeon
- Oliver Weeger
- Utz Wever
- Volker Mehrmann
- Lorenz T. Biegler
In Statistical and Nonlinear Physics
- Patrick Kürschner
- Peter Benner
- Jens Saak
- Bernd Simeon
- Oliver Weeger
- Utz Wever
- Volker Mehrmann
- Valeria Simoncini
Citations in the corpus
- Control and Optimization with Differential-Algebraic Constraints (2012, background): “This is mainly due to the fact that the constraints and physical properties, like stability and passivity, must be respected in the approximated model to achieve physically meaningful results [1, 35].”
- Self-Generating and Efficient Shift Parameters in ADI Methods for Large Lyapunov and Sylvester Equations (2014, methodology): “Note that there are also LRADI approaches for handling DAE systems of higher indices [26], e.”
- A Survey on Model Reduction of Coupled Systems (2008, unknown): “Numerical examples are given.”
- On the use of modal derivatives for nonlinear model order reduction (2016, methodology): “Specifically in state-space formulations, balanced truncation is a favourite method [2, 3, 4, 5, 6], since it guarantees the observability and the stability of the system [7].”