返回Google圖書搜尋

Clustering-based Model Order Reduction for Multi-agent Systems with General Linear Time-invariant Agents

出版	Max Planck Institute for Dynamics of Complex Technical Systems, 2016
URL	http://books.google.com.hk/books?id=l7vpuQEACAAJ&hl=&source=gbs_api

註釋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.