Multitime Scale Consensus Algorithm of Multiagent Systems With Binary-Valued Data Under Tampering Attacks
Ruizhe Jia, Ting Wang, Wenchao Xue, Jin Guo, Yanlong Zhao
Abstract
The focus of this article is on the consensus problem of the multiagent system (MAS) with binary-valued quantized data under data tampering attacks. First, the properties of data tampering attacks are analyzed, and sufficient conditions are provided under which the attacks can effectively disrupt the consensus algorithm. Subsequently, inspired by the scheme of hierarchical estimation, a multitime scale consensus algorithm is proposed, enabling the MAS to achieve mean square consensus in the presence of tampering attacks. Next, the convergence speed of the consensus algorithm is analyzed, and it is demonstrated that the algorithm designed in this article retains the same upper bound for convergence speed under attacks as the two-time scale consensus algorithm without attacks. Finally, the effectiveness of the proposed method are validated through a signal frequency consensus experiment of the uncrewed aerial vehicles swarm system.