Model-order reduction of large-scale second-order MIMO dynamical systems via a block second-order Arnoldi method

Authors:
Yiqin Lin;Liang Bao;Yimin Wei
Affiliations:
Department of Mathematics and Computational Science, Hunan University of Science and Engineering, Yongzhou, P.R. China;Institute of Mathematics, School of Mathematical Sciences, Fudan University, Shanghai, P.R. China;Ministry of Education, Key Laboratory of Mathematics for Nonlinear Sciences (Fudan University), P.R. China
Venue:
International Journal of Computer Mathematics
Year:
2007

Citing 6
Cited 0

Robust and optimal control

Robust and optimal control
Krylov-subspace methods for reduced-order modeling in circuit simulation

Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. III: linear algebra
Krylov subspace techniques for reduced-order modeling of large-scale dynamical systems

Applied Numerical Mathematics
Model Reduction of MIMO Systems via Tangential Interpolation

SIAM Journal on Matrix Analysis and Applications
Dimension Reduction of Large-Scale Second-Order Dynamical Systems via a Second-Order Arnoldi Method

SIAM Journal on Scientific Computing
Approximation of Large-Scale Dynamical Systems (Advances in Design and Control) (Advances in Design and Control)

Approximation of Large-Scale Dynamical Systems (Advances in Design and Control) (Advances in Design and Control)

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a structure-preserving model-order reduction method for solving large-scale second-order MIMO dynamical systems. It is a projection method based on a block second-order Krylov subspace. We use the block second-order Arnoldi (BSOAR) method to generate an orthonormal basis of the projection subspace. The reduced system preserves the second-order structure of the original system. Some theoretical results are given. Numerical experiments report the effectiveness of this method.