Low Complexity Distributed Adaptive Bipartite Tracking Consensus Control of Nonlinear Multi‐Agent Systems Against Sensor Deception Attacks

ABSTRACT In this study, a novel perspective on an adaptive bipartite consensus tracking scheme for multi‐agent systems (MASs) in the face of sensor attacks is presented. The bipartite consensus tracking problem of MASs is transformed into the tracking problem of a single agent based on the shortest path method, and the assumption of structural balance for a digraph is removed. A significant challenge encountered in this article is that the original sensor measurement states cannot be directly and accurately measured and used after being subjected to malicious deception attacks. Therefore, to solve this issue, a novel coordinate transformation method including compromised states is proposed. Furthermore, the Nussbaum function is only introduced in the final step to avoid the effects of unknown attack gains resulting from deception attacks in the system, and a set of tuning functions are designed to resolve the singularity issue encountered during the adaptive iterative process of previous studies. A distributed security control scheme is designed using backstepping and Lyapunov stability theory, ensuring that all closed‐loop system signals remain globally and uniformly bounded. Simulation results with a group of single‐link robots validate the efficacy of the presented approach.