Gnecco, Giorgio and Morisi, Rita and Bemporad, Alberto Sparse solutions to the average consensus problem via L1-Norm regularization of the fastest mixing Markov-Chain problem. In: Proceedings of the 53rd Annual Conference on Decision and Control (CDC). IEEE, pp. 2228-2233. ISBN 978-1-4799-7746-8 (2014)
Full text not available from this repository.Abstract
In the “consensus problem” on multi-agent systems, in which the states of the agents are “opinions”, the agents aim at reaching a common opinion (or “consensus state”) through local exchange of information. An important design problem is to choose the degree of interconnection of the subsystems so as to achieve a good trade-off between a small number of interconnections and a fast convergence to the consensus state, which is the average of the initial opinions under mild conditions. This paper addresses this problem through l1-norm regularized versions of the well-known fastest mixing Markov-chain problem, which are investigated theoretically. In particular, it is shown that such versions can be interpreted as “robust” forms of the fastest mixing Markov-chain problem. Theoretical results useful to guide the choice of the regularization parameters are also provided, together with a numerical example.
| Item Type: | Book Section |
|---|---|
| Identification Number: | 10.1109/CDC.2014.7039729 |
| Additional Information: | 53rd Annual Conference on Decision and Control (CDC), held in Los Angeles (USA) 15-17 December 2014 |
| Uncontrolled Keywords: | Optimization, Sensor networks, Linear systems |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Ms T. Iannizzi |
| Date Deposited: | 13 Jan 2015 15:04 |
| Last Modified: | 18 Feb 2015 12:06 |
| URI: | http://eprints.imtlucca.it/id/eprint/2480 |
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