|Publisher DOI:||10.1109/CDC.2018.8619131||Title:||A Novel Sequence Weighting Method for First-Order Consensus Problems||Language:||English||Authors:||Mirali, Furugh
|Issue Date:||18-Jan-2019||Source:||Proceedings of the IEEE Conference on Decision and Control (2018-December): 97-102 (2019-01-18)||Journal or Series Name:||Proceedings of the IEEE Conference on Decision & Control||Abstract (english):||In this paper we present a novel method for constructing stochastic weighting matrices with the help of a finite sequence that can be chosen according to the application in a distributed manner. In addition, we propose three algorithms that determine how every agent decides on assigning these weights to its neighbours. Then, the so-called sequence weighting method is compared with other existing approaches for the special case of a one-dimensional lattice graph. For this purpose, we derive the characteristic polynomial of a quasi- Toeplitz matrix. Considering the sequence weighting method we calculate a bound for the second greatest eigenvalue that can be bounded away from 1 independent of the network size. Using a recently reported result about uniform packet loss, we show that bounds on the convergence speed not only hold in the loss-free case, but also when uniform packet loss occurs. Simulation results with non-uniform packet loss confirm a better performance using the sequence weighting method in comparison to existing strategies. © 2018 IEEE.||Conference:||57th IEEE Conference on Decision and Control||URI:||http://hdl.handle.net/11420/2195||ISBN:||978-153861395-5||ISSN:||0743-1546||Institute:||Regelungstechnik E-14||Type:||InProceedings (Aufsatz / Paper einer Konferenz etc.)||Project:||Multi-Agent Systems|
|Appears in Collections:||Publications without fulltext|
Show full item record
checked on Sep 29, 2020
Add Files to Item
Note about this record
Items in TORE are protected by copyright, with all rights reserved, unless otherwise indicated.