Prescribed-time privacy-preserving bipartite consensus of multiagent systems via edge-event-triggered method

Abstract

This paper investigates the prescribed-time privacy-preserving bipartite consensus problem of multiagent systems (MASs). A novel edge-event-triggered prescribed-time privacy-preserving consensus protocol is proposed to achieve accurate bipartite consensus of MASs in a prescribed time while protecting the agents’ states from being obtained by curious agents. To mask the agents’ states, a new edge-based output mask function is designed. This function allows the agents to set different private parameters for different neighbors, effectively preventing the curious agents from accessing all the information used by the protected agent, thereby achieving a better privacy preservation effect. In addition, an edge-based dynamic event-triggered strategy (ETS) is designed to save communication resources while further reducing the risk of privacy leakage. Sufficient conditions that can guarantee accurate bipartite consensus of MASs in a prescribed time and prevent the agents’ states from being reconstructed by curious agents are obtained. Furthermore, the Zeno behavior is excluded throughout the period except for the prescribed time. Finally, numerical simulations validate the theoretical results.