Decentralized Laplacian eigenvalues estimation for networked multi-agent systems

Franceschelli, Mauro; Gasparri, Andrea; Giua, Alessandro; Seatzu, Carla

doi:10.1109/cdc.2009.5400723

Cited by 58 publications

(59 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [7] Franceschelli et al presented a necessary and su cient condition to verify observability and controllability of a leader-follower network of mobile vehicles with unknown topology based on the algorithm in [6] and its extension in this paper.…”

Section: Related Workmentioning

confidence: 99%

“…In [19] Sahai et al presented an approach building on the idea of [6] for the application of clustering. The authors propose a local interaction rule formally equivalent to the wave equation discretized in time and space and show that the wave equation method , can be used to cluster a graph by estimating the sign of the coe cients of the discrete Fourier transform corresponding to the second smallest eigenvalue.…”

Section: Related Workmentioning

confidence: 99%

“…• We propose an improvement with respect to [6] so that no component at null frequency exists in the evolution of the agents' state. The removal of the DC component allows the straightforward application of frequency estimation algorithms such as the one in [4].…”

Section: Introductionmentioning

confidence: 99%

“…• We extend [6] by characterizing analytically the amplitude and phase of the oscillations as function of the eigenvectors of the Laplacian and the initial conditions.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Decentralized estimation of Laplacian eigenvalues in multi-agent systems

et al. 2013

Self Cite

View full text Add to dashboard Cite

)>IJH=?J 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 nite number of frequencies at which the signal oscillates.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…• We extend [6] by characterizing analytically the amplitude and phase of the oscillations as function of the eigenvectors of the Laplacian and the initial conditions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Decentralized estimation of Laplacian eigenvalues in multi-agent systems

et al. 2013

Self Cite

View full text Add to dashboard Cite

show abstract

“…The Laplacian eigenvalues are estimated in [3] by making the agents execute a local interaction rule that makes their states oscillate at frequencies corresponding to these eigenvalues. Agents use the Fast Fourier Transform (FFT) on their states to identify these eigenvalues.…”

Section: Introductionmentioning

confidence: 99%

Distributed algebraic connectivity estimation for undirected graphs with upper and lower bounds

Aragüés¹,

Shi²,

Dimarogonas³

et al. 2014

Automatica

View full text Add to dashboard Cite

The algebraic connectivity of the graph Laplacian plays an essential role in various multi-agent control systems. In many cases a lower bound of this algebraic connectivity is necessary in order to achieve a certain performance. Lately, several methods based on distributed Power Iteration have been proposed for computing the algebraic connectivity of a symmetric Laplacian matrix. However, these methods cannot give any lower bound of the algebraic connectivity and their convergence rates are often unclear. In this paper, we present a distributed algorithm for estimating the algebraic connectivity for undirected graphs with symmetric Laplacian matrices. Our method relies on the distributed computation of the powers of the adjacency matrix and its main interest is that, at each iteration, agents obtain both upper and lower bounds for the true algebraic connectivity. It was proven that both bounds successively approach the true algebraic connectivity with the convergence speed no slower than O(1/k).

show abstract

A Filter‐based Clock Synchronization Protocol for Wireless Sensor Networks

Yang

2018

Asian Journal of Control

View full text Add to dashboard Cite

Clock parameters in wireless sensors experience slow changes due to low-cost construction and environmental conditions. In this paper, a filter-based distributed protocol, called FBP, is proposed to dynamically achieve clock synchronization for wireless sensor networks. The idea of FBP is derived from a first-order filter which is robust to environmental noises. The proposed protocol is fully distributed, meaning that each node relies only on its local clock readings and reading announcements from its neighbouring sensor nodes. This will allow the proposed protocol applicable to large sensor networks. By applying FBP, the compensated clock skews can be bounded into a small steady-state error. Numerical simulations show that the proposed protocol yields better performances in both convergence property and synchronization accuracy.

show abstract

Decentralized Laplacian eigenvalues estimation for networked multi-agent systems

Cited by 58 publications

References 17 publications

Decentralized estimation of Laplacian eigenvalues in multi-agent systems

Decentralized estimation of Laplacian eigenvalues in multi-agent systems

Distributed algebraic connectivity estimation for undirected graphs with upper and lower bounds

A Filter‐based Clock Synchronization Protocol for Wireless Sensor Networks

Contact Info

Product

Resources

About