Distributed Estimation and Motion Control in Multi-agent Systems under Multiple Attacks

This paper addresses the problem of distributed estimation and motion control (DEMC) in multi-agent systems (MASs) with both linear and Lipschitz nonlinear dynamics. Unlike conventional DEMC methods designed for MASs under ideal conditions, this work investigates scenarios where all agents are vulnerable to various forms of attacks. The considered attacks comprise false-data injection (FDI) attacks and denial of service (DoS) attacks that affect the communication channels among agents to destabilize the MAS. Also, the unbounded actuator attacks which exist in practical environments to intentionally degrade the MAS performance is considered. To cope with these kinds of attacks, two novel resilient approaches are established aimed at estimating and following a mobile target under attacks. The proposed distributed attack-resilient control strategies are designed based on a dual-layer structure, guaranteeing effective DEMC with an ultimately bounded error. The results from two simulation examples are provided to validate the presented algorithms.