Publisher DOI: | 10.1109/CDC.2018.8619131 | Title: | A Novel Sequence Weighting Method for First-Order Consensus Problems | Language: | English | Authors: | Mirali, Furugh Werner, Herbert |
Issue Date: | 18-Jan-2019 | Source: | Proceedings of the IEEE Conference on Decision and Control (2018-December): 97-102 (2019-01-18) | 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. |
Conference: | 57th IEEE Conference on Decision and Control, CDC 2018 | URI: | http://hdl.handle.net/11420/2195 | ISBN: | 978-153861395-5 | ISSN: | 0743-1546 | Journal: | Proceedings of the IEEE Conference on Decision & Control | Institute: | Regelungstechnik E-14 | Document Type: | Chapter/Article (Proceedings) | Project: | Multi-Agent Systems |
Appears in Collections: | Publications without fulltext |
Show full item record
Add Files to Item
Note about this record
Cite this record
Export
Items in TORE are protected by copyright, with all rights reserved, unless otherwise indicated.