A generalization of the graph Laplacian with application to a distributed consensus algorithm - Zhai, Guisheng (Zielona Góra: Uniwersytet Zielonogórski)
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.
Keywords: graph Laplacian; generalized graph Laplacian; adjacency weights; distributed consensus algorithm; cooperative control