Model-order reductions for MIMO systems using global Krylov subspace methods

Chia-Chi Chu, Ming-Hong Lai and Wu-Shiung Feng

Mathematics and Computers in Simulation (MATCOM), 2008, vol. 79, issue 4, 1153-1164

Abstract: This paper presents theoretical foundations of global Krylov subspace methods for model order reductions. This method is an extension of the standard Krylov subspace method for multiple-inputs multiple-outputs (MIMO) systems. By employing the congruence transformation with global Krylov subspaces, both one-sided Arnoldi and two-sided Lanczos oblique projection methods are explored for both single expansion point and multiple expansion points. In order to further reduce the computational complexity for multiple expansion points, adaptive-order multiple points moment matching algorithms, or the so-called rational Krylov space method, are also studied. Two algorithms, including the adaptive-order rational global Arnoldi (AORGA) algorithm and the adaptive-order global Lanczos (AOGL) algorithm, are developed in detail. Simulations of practical dynamical systems will be conducted to illustrate the feasibility and the efficiency of proposed methods.

Keywords: Model-order reduction; Padé approximations; Global Krylov subspace; Multiple points moment matching; Rational Krylov subspace (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:79:y:2008:i:4:p:1153-1164

DOI: 10.1016/j.matcom.2007.09.007

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