Observer-Based Data-Driven Consensus Control for Nonlinear Multi-Agent Systems against DoS and FDI attacks

TL;DR

This paper proposes a novel distributed data-driven control framework with attack-resilient observers to achieve consensus in nonlinear multi-agent systems under simultaneous FDI and DoS attacks, ensuring stability and improved resilience.

Contribution

It introduces a new attack-resilient consensus control method combining observers for FDI, disturbances, and DoS attacks, with rigorous stability analysis and validation.

Findings

Enhanced attack resilience in multi-agent consensus

Effective estimation of FDI and DoS attacks

Validated improved performance through numerical examples

Abstract

Existing data-driven control methods generally do not address False Data Injection (FDI) and Denial-of-Service (DoS) attacks simultaneously. This letter introduces a distributed data-driven attack-resilient consensus problem under both FDI and DoS attacks and proposes a data-driven consensus control framework, consisting of a group of comprehensive attack-resilient observers. The proposed group of observers is designed to estimate FDI attacks, external disturbances, and lumped disturbances, combined with a DoS attack compensation mechanism. A rigorous stability analysis of the approach is provided to ensure the boundedness of the distributed neighborhood estimation consensus error. The effectiveness of the approach is validated through numerical examples involving both leaderless consensus and leader-follower consensus, demonstrating significantly improved resilient performance compared to existing data-driven control approaches.