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 
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 
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