Distributed Nash Equilibrium Seeking of Second-Order Multi-Agent Systems Under Unknown False Data Injection Attacks

This paper investigates resilient adaptively distributed Nash Equilibrium (NE) seeking problems for noncooperative games of double-integrator players under malicious attacks, i.e., false data injection (FDI) attacks. Different from distributed NE seeking in many existing literature under ideal environments, it is challenging to achieve the NE seeking under unknown and unbounded FDI attacks. An attack-resilient NE seeking architecture that is distributed, is established by means of the consensus-based gradient play together with an attack identifier to deal with the impacts of FDI attacks. Another key characteristic is that malicious FDI attacks are allowed to be completely unknown and unbounded. The global asymptotic convergence of the proposed distributed NE seeking algorithm to-ward the NE is guaranteed. Lastly, numerical simulation results are provided to illustrate the effectiveness of the proposed algorithms.