|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||Conference:||57th IEEE Conference on Decision and 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.||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.)|
|Appears in Collections:||Publications without fulltext|
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