Consensus of Multi-Agent Systems via Aperiodically Intermittent Sampling Stochastic Noise

In this paper, stabilization by aperiodically intermittent sampling stochastic noise is introduced as a new way of solving the consensus problem of a class of homogeneous multi-agent systems. A multiplicative noise is designed as a control input to stabilize the error system of the multi-agents. The average noise control rate (ANCR) is employed to estimate the working time of aperiodically intermittent noise, which reduces the conservativeness caused by the irregular noise working and rest time distribution. A novel piecewise analysis technique (PAT) is adopted to estimate the mean square of the error state, which allows for the larger noise sampling period. Meanwhile, the sufficient criteria to ensure almost sure stability of the error system are obtained, as well as the transcendental equation concerning the noise sampling period
$\tau $
and the ANCR
$\Gamma $
. Finally, the numerical simulation demonstrates the efficiency and accuracy of the proposed method.