Decentralized estimation of Laplacian eigenvalues in multi-agent systems
FRANCESCHELLI, MAURO;GIUA, ALESSANDRO;SEATZU, CARLA
2013-01-01
Abstract
In this paper, we present a decentralized algorithm to estimate the eigenvalues of the Laplacian matrix that encodes the network topology of a multi-agent system. We consider network topologies modeled by undirected graphs. The basic idea is to provide a local interaction rule among agents so that their state trajectory is a linear combination of sinusoids oscillating only at frequencies function of the eigenvalues of the Laplacian matrix. In this way, the problem of decentralized estimation of the eigenvalues is mapped into a standard signal processing problem in which the unknowns are the finite number of frequencies at which the signal oscillates.Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.