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Clustering-based model order reduction for multi-agent systems with general linear time-invariant agents / Petar Mlinarić, Sara Grundel, Peter Benner
VerfasserMlinarić, Petar ; Grundel, Sara ; Benner, Peter
KörperschaftMax-Planck-Institut für Dynamik Komplexer Technischer Systeme
ErschienenMagdeburg : Max Planck Institute for Dynamics of Complex Technical Systems, January 22, 2016
Umfang1 Online-Ressource (11 Seiten = 0,29 MB) : Diagramm
SpracheEnglisch
SerieMax Planck Institute Magdeburg Preprints ; 16-02
URNurn:nbn:de:gbv:3:2-64518 
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Clustering-based model order reduction for multi-agent systems with general linear time-invariant agents [0.29 mb]
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Abstract: In this paper we extend our clustering-based model order reduction method for multi-agent systems with single-integrator agents to the case where the agents have identical general linear time-invariant dynamics. The method consists of the Iterative Rational Krylov Algorithm for finding a good reduced order model and the QR decomposition-based clustering algorithm to achieve structure preservation by clustering agents. Compared to the case of single-integrator agents we modified the QR decomposition with column pivoting inside the clustering algorithm to take into account the block-column structure. We illustrate the method on small and large-scale examples.