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Kalman filtering for networked multi-agent systems with random packet dropouts

This paper considers consensus of multi-agent systems (MASs) with random packet dropout based on Kalman filter. The Kalman filter is used to estimate current state of agents due to immeasurable output or state data. The relationship between packet dropout rate and the consensus ability of MASs is obtained. And the critical rate of packet dropout is gained. One step prediction method which can decrease the rate of packet dropout is presented. Numerical examples illustrate the effectiveness of the proposed results.