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Exploiting the Agent's Memory in Asymptotic and Finite-time Consensus over Multi-agent Networks

By Pasolini G., Dardari D. and Kieffer M.


This paper proposes two average consensus algorithms exploiting the memory of agents. The performance of the proposed as well as of several state-of-the-art consensus algorithms is evaluated considering different communication ranges, and evaluating the impact of transmission errors. To compare asymptotic and finite-time average consensus schemes, the \u3f5-convergence time is adopted for a fair comparison. A discussion about memory requirements, transmission overhead, a priori information on network topology, and robustness to errors is provided

Topics: Average consensus, asymptotic consensus, finite-time consensus, convergence time
Publisher: 'Institute of Electrical and Electronics Engineers (IEEE)'
Year: 2020
DOI identifier: 10.1109/TSIPN.2020.3002613
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