Resilient Estimation for Linear and Adaptive Distributed Observer Based on Redundant Information Flow

This addresses the consensus problem of a leader-following multi-agent system (MAS) in the presence of attacked nodes. A distributed observer is proposed deploying the subsequence-reduced algorithm (SRA) based on a thorough analysis of the attack pattern and scope of the cyber-attack model. By exploiting the robustness of the network communication graph and the redundant information, the proposed observer effectively eliminates cyber-attack impacts and achieves consensus convergence. The consensus property and attack rejection capability are analyzed by Lyapunov theory for both subsequence-reduced linear distributed observer (SRLDO) and the subsequence-reduced adaptive linear distributed observer (SRALDO). The effectiveness of the proposed observer is verified through a two-link robotic arm cluster experiment with comparisons to recent methods.