Event-triggered privacy preserving consensus control with edge-based additive noise

TL;DR

This paper presents a novel event-triggered consensus control method for multi-agent systems that preserves privacy by adding noise to communications and reduces communication frequency through event-triggering, ensuring convergence.

Contribution

It introduces a new privacy-preserving, event-triggered consensus scheme with noise addition and stochastic protocols, enhancing privacy and efficiency in multi-agent systems.

Findings

The scheme guarantees asymptotic consensus under noise and event-triggering.

The proposed protocol effectively balances privacy, communication reduction, and convergence accuracy.

Numerical simulations confirm the scheme's effectiveness and robustness.

Abstract

In this article, we investigate the distributed privacy preserving weighted consensus control problem for linear continuous-time multi-agent systems under the event-triggering communication mode. A novel event-triggered privacy preserving consensus scheme is proposed, 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, which avoids the frequent real-time communication. 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. By using the tools of stochastic analysis and graph theory, the asymptotic property and convergence accuracy of consensus error is analyzed. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed scheme.