基于状态分解的多智能体隐私保护一致性控制

Privacy-preserving Consensus Control of Multi-agents via State Decomposition

  • 摘要: 针对2阶连续时间多智能体系统中节点的隐私保护问题,提出了一种基于状态分解的一致性控制方法。首先,将每个节点随机分解为两个子节点,节点之间的通信只交换其中一个子节点的信息,从而保护节点的隐私。其次,在具有有向通信拓扑的2阶系统中,设计了动态一致性和静态一致性的控制协议,基于矩阵理论分析了系统的稳定性和收敛性,并将结论扩展到具有无向通信拓扑的系统和具有领导者和跟随者的系统。仿真结果表明,所提方法能够在保护系统隐私的同时实现精确的一致性控制。

     

    Abstract: To address the issue of privacy preserving for nodes in second-order continuous-time multi-agent systems, we propose a consensus control method based on state decomposition. First, we randomly decompose each node into two subnodes, with internode communication for exchanging information from only one of the subnodes, thereby preserving the privacy of the individual nodes. Second, we present dynamic and static consensus control protocols for second-order systems with directed communication topologies. Based on the matrix theory, we analyze the stability and convergence of the system and extend the conclusions to systems with undirected communication topologies and leader-follower configurations. The simulation results demonstrate that the proposed method achieves accurate consensus control while preserving system privacy.

     

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