Exploiting the Agent's Memory in Asymptotic and Finite-time Consensus over Multi-agent Networks
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
Average consensus, asymptotic consensus, finite-time consensus, convergence time
Publisher: 'Institute of Electrical and Electronics Engineers (IEEE)'
DOI identifier: 10.1109/TSIPN.2020.3002613
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