Brief paper: Krylov projection framework for Fourier model reduction

Authors:
Serkan Gugercin;Karen Willcox
Affiliations:
Department of Mathematics, Virginia Tech, 442 McBryde Hall, Blacksburg, VA 24061-0123, USA;Department of Aeronautics and Astronautics, MIT, 77 Massachusetts Avenue, Room 37-447, Cambridge, MA 02139, USA
Venue:
Automatica (Journal of IFAC)
Year:
2008

Citing 4
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Abstract

This paper analyzes the Fourier model reduction (FMR) method from a rational Krylov projection framework and shows how the FMR reduced model, which has guaranteed stability and a global error bound, can be computed in a numerically efficient and robust manner. By monitoring the rank of the Krylov subspace that underlies the FMR model, the projection framework also provides an improved criterion for determining the number of Fourier coefficients that are needed, and hence the size of the resulting reduced-order model. The advantages of applying FMR in the rational Krylov projection framework are demonstrated on a simple example.