Paper Info
Title
Speeding up finite-time consensus via minimal polynomial of a weighted graph — A numerical approach
Abstract
This work proposes an approach to speed up finite-time consensus algorithm using the weights of a weighted Laplacian matrix. It is motivated by the need to reach consensus among states of a multi-agent system in a distributed control/optimization setting. The approach is an iterative procedure that finds a low-order minimal polynomial that is consistent with the topology of the underlying graph. In general, the lowest-order minimal polynomial achievable for a network system is an open research problem. This work proposes a numerical approach that searches for the lowest order minimal polynomial via a rank minimization problem using a two-step approach: the first being an optimization problem involving the nuclear norm and the second a correction step. Convergence of the algorithm is shown and effectiveness of the approach is demonstrated via several examples.
Year
DOI
Venue
2017
10.1016/j.automatica.2018.03.067
Automatica
Keywords
Field
DocType
Laplacian matrix,Rank minimization,Minimal polynomial,Consensus algorithm
Convergence (routing),Graph,Laplacian matrix,Mathematical optimization,Matrix norm,Minimal polynomial (linear algebra),Optimization problem,Mathematics,Speedup,Finite time
Journal
Volume
Issue
ISSN
93
93
0005-1098
Citations 
PageRank 
References 
0
0.34
6
Authors
2
Name
Order
Citations
PageRank
Zheming Wang1308.12
Chong-Jin Ong271656.26