Event-Triggered Privacy-Preserving Consensus Control With Edge-Based Additive Noise
Limei Liang, Ruiqi Ding, Shuai Liu, Rong Su
Abstract
In this paper, we propose a novel event-triggered distributed privacy preserving consensus scheme for linear continuous-time multi-agent systems, which can be divided into three phases. First, for each agent, an event-triggered mechanism is designed to determine whether the current state is transmitted to the corresponding neighbor agents. Then, to protect the privacy of initial states from disclosure, the edge-based mutually independent standard white noise is added to each communication channel. Further, to attenuate the effect of noise on consensus control, we propose a stochastic approximation type protocol for each agent. Based on stochastic analysis and graph theory, we analyze the asymptotic property and convergence accuracy of the consensus error, the privacy of the privacy preserving scheme and the Zeno behavior of the event-triggered mechanism. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed scheme.