Paper Info
Title
Balanced truncation model order reduction in limited time intervals for large systems.
Abstract
In this article we investigate model order reduction of large-scale systems using time-limited balanced truncation, which restricts the well known balanced truncation framework to prescribed finite time intervals. The main emphasis is on the efficient numerical realization of this model reduction approach in case of large system dimensions. We discuss numerical methods to deal with the resulting matrix exponential functions and Lyapunov equations which are solved for low-rank approximations. Our main tool for this purpose are rational Krylov subspace methods. We also discuss the eigenvalue decay and numerical rank of the solutions of the Lyapunov equations. These results, and also numerical experiments, will show that depending on the final time horizon, the numerical rank of the Lyapunov solutions in time-limited balanced truncation can be smaller compared to standard balanced truncation. In numerical experiments we test the approaches for computing low-rank factors of the involved Lyapunov solutions and illustrate that time-limited balanced truncation can generate reduced order models having a higher accuracy in the considered time region.
Year
DOI
Venue
2018
10.1007/s10444-018-9608-6
Adv. Comput. Math.
Keywords
Field
DocType
Lyapunov equation, Rational Krylov subspaces, Model order reduction, Balanced truncation, Matrix exponential, 15A16, 15A18, 15A24, 65F60, 93A15, 93C
Krylov subspace,Lyapunov function,Truncation error,Mathematical optimization,Mathematical analysis,Model order reduction,Truncation error (numerical integration),Numerical analysis,Matrix exponential,Mathematics,Eigenvalues and eigenvectors
Journal
Volume
Issue
ISSN
44
6
1019-7168
Citations 
PageRank 
References 
5
0.49
16
Authors
1
Name
Order
Citations
PageRank
Patrick Kürschner1375.29