Meth­ods of Model Order Re­duc­tion (MOR)

Registration

The course MOR will take place in SoSe 2025 as online sessions via Microsoft Office 365 / Teams. To take part in the course you have to join the "Methods of Model Order Reduction" team using the team code duwe51f.

Instructions for using Microsoft Teams .

  • In MS Teams, click "Join a team or create a team".
  • Then enter the team code duwe51f under "Join a team with a code" and then click "Join team".

Lecture

Instructor: PD Dr.-Ing. habil. Ortwin Farle
Location: On appointment.
Time: On appointment.
Please contact Prof. Dr. Romanus Dyczij-Edlinger.
Extent: 15 weeks per 2 weekly hours.

Tutorial

Location: On appointment.
Time: On appointment.
Please contact Prof. Dr. Romanus Dyczij-Edlinger.
Extent: 15 weeks per 1 weekly hour.

Documents:

Download lecture notes*
Download exercise sheets*

Correlation to curriculum:

Extension to Master Systems Engineering
Extension to Master Mechatronik
Deepening lecture Master COMET

Admission requirements:

None.

Evaluation / Examination:

Oral exam
Here you will find the underlying grading scheme .

Effort:

Lecture
Homework
Total		45 h
75 h
120 h

Module grade:

Oral exam100 %

Educational objective

  • Students are familiar with the common model order reduction methods.
  • To be able to expediently choose from different model order reduction methods.
  • To know how to implement the methods in a numerically robust way.
  • To be aware of the effects of model order reduction methods on important system properties.

    Topics

    • Balanced Truncation.
    • Krylov subspace methods.
    • Multi‐point methods: rational Krylov methods, proper orthogonal decomposition, reduced basis method.
    • Parametric model order reduction.
    • Preservation of important system properties, i.e. reciprocity, passivity, causality etc.

    Further information

    • Language of instruction: Englisch
    • A. C. Antoulas. Approximation of Large-Scale Dynamical Systems. SIAM 2005
    • L. N. Trefethen, D. Bau III. Numerical Linear Algebra. SIAM 1997
    • G. E. Dullerud, F. Paganini. A Course in Robust Control Theory. Springer 2000
    • L. Debnath, P. Mikusinski: Introduction to Hilbert Spaces, 3rd edition. Elsevier 2005.