Model reduction and approximation methods

Model reduction and approximation methods

Basic Information

M132 (2+1+1) - 6 ECTS credits

Introduce students to model reduction and approximation methods for numerical determination of reduced model. Study basic methods for model reduction and solution of large-scale matrix equations. Investigate and interpret problems for model reduction that arise in applications. Implement numerical methods for model reduction on examples. Use programing packages for implementation of studied methods and for testing of methods in different real life examples.

You can access the course content at the following link: PDF

Teachers

Basic literature

  1. A. C. Antoulas, Approximation of Large-Scale Dynamical Systems, SIAM, Philadelphia, 2005.
  2. W. H. Schilders, H. A. Vorst, J. Rommes, Model Order Reduction: Theory, Research Aspects and Applications, Springer, 2008.

Additional literature

  1. B. N. Datta, Numerical Methods for Linear Control Systems, Academic Press, 2003.
  2. K. Zhou, J. C. Doyle, K. Glover, J. C. Doyle, Robust and optimal control, Prentice Hall, 1995.
  3. K. Zhou, J. C. Doyle, Essentials of robust control, Prentice Hall, 1997.
  4. G. E. Dullerud, F. Paganini, A Course in Robust Control Theory, Springer Verlag, 2000.
  5. F. L. Lewis, V. S. Syrmos, Optimal control, Wiley, Hoboken, 2012.

 

Teaching materials

The materials are available on the internal Teams channel of the course, through which all internal communication takes place. Students are required to register on the course’s Teams channel. The channel code for joining the course can be found in the schedule.