International Journal of applied mathematics and computer science

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Paper details

Number 2 - June 2015
Volume 25 - 2015

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

Guisheng Zhai

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.

graph Laplacian, generalized graph Laplacian, adjacency weights, distributed consensus algorithm, cooperative control