Distributed robust-multivariate-observer-based FDI attacks estimation for nonlinear multi-agent systems with directed graphs

This article investigates the distributed robust estimation problem for false data injection (FDI) attacks in nonlinear multi-agent systems with directed graphs. To approximate the realistic attack scenario, the case where both the actuator network channel and sensor network channel suffering from FDIs are considered, and the attack signals contain time-varying circumstances. A novel distributed robust-multivariate-observer (DRMO) strategy is developed such that the online estimation of FDI attack dynamics can be realized with the partially unknown nonlinear dynamics, attack transient increments, and disturbances impact being eliminated. The designed DRMO scheme only depends on the received compromised/uncompromised measurement output information on the account that whole state information cannot be measured directly. Finally, two simulation examples, including a network of four one-link flexible joint manipulator systems with comparisons to existing methods, are given to show the effectiveness of the proposed scheme.