A generalization of the graph laplacian with application to a distributed consensus algorithm

研究成果: Article査読

3 被引用数 (Scopus)

抄録

In order to describe the interconnection among agents with multi-dimensional states, we generalize the notion of a graph Laplacian by extending the adjacency weights (or weighted interconnection coefficients) from scalars to matrices. More precisely, we use positive definite matrices to denote full multi-dimensional interconnections, while using nonnegative definite matrices to denote partial multi-dimensional interconnections. We prove that the generalized graph Laplacian inherits the spectral properties of the graph Laplacian. As an application, we use the generalized graph Laplacian to establish a distributed consensus algorithm for agents described by multi-dimensional integrators.

本文言語English
ページ(範囲)353-360
ページ数8
ジャーナルInternational Journal of Applied Mathematics and Computer Science
25
2
DOI
出版ステータスPublished - 2015 6 1

ASJC Scopus subject areas

  • コンピュータ サイエンス(その他)
  • 工学(その他)
  • 応用数学

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