Model Order Reduction Lab (MORLab)!
On our website we offer you detailed insight into our research activities as well as numerous downloads of publications and research code. Do you have questions? Don't hesitate to contact us!
What is Model Order Reduction?
In order to meet the requirements of today's applications and system designs, a common result of accurate modeling, e. g. by finite element methods, is a large number (few hundred thousands) of first or second order differential equations. With the current digital computers, it is very difficult or even impossible to handle these large-scale systems, mainly due to the limitations in memory, accuracy or executing time. In order to be able to handle such systems for the purpose of simulation, controller design, optimization and prediction, it is advisable to find a reduced order model that approximates the behavior of the original system while preserving some of its original properties like passivity, stability, and structure.
Our Fields of Research
In the MORLab we deal with the following topics of model order reduction:
- MOR for parametric non-linear mechanical systems
- Port-Hamiltonian Systems
- Krylov Subspace Methods
- Parametric Model Order Reduction
- Nonlinear Model Order Reduction
In addition we develop software tools for the analysis and reduction of large-scale models: