Open Privacy-Preserving Consensus via State Decomposition

Generally, the majority of the achievements on privacy preservation of consensus always anchor that the number of interacting agents is permanent. Nevertheless, this is overly restrictive in many multi-agent systems (MAS) applications where agent removal or joining may arise at any operational instant. In light of this, the current article studies the privacy-preserving problem of open MAS. To achieve this, we propose an open state-decomposition-based algorithm that not only assures the consensus but also achieves the privacy preservation of the initial states, despite the agent removal or joining. It is shown that the proposed algorithm can mask the true values in an open communication environment, thus preventing honest-but-curious agents and external eavesdroppers from accessing sensitive information. Finally, the effectiveness of the derived results, as well as the proposed algorithm, are illustrated via numerical simulations.