Observer-Based Attack Detection and Data-Driven Resilient Control for Heterogeneous Nonlinear Nonaffine Mass Under FDI Attacks

Abstract

The attack detection and data-driven resilient control problem for heterogeneous nonlinear nonaffine multi-agent systems (MASs) in the presence of intermittent false data injection (FDI) attacks is investigated in this article. First, an attack detection and isolation mechanism based on the distributed observer are designed to determine the attack signals and isolate the attacked communication links in time. Then, in order to solve the problem of the unknown system model, the dynamic linearization method is used to convert the nonlinear nonaffine MASs into an equivalent linear data model. Further, based on the linear data model, the data-driven resilient controller with the attack isolation mechanism is designed to achieve the leader-following tracking control objective. Finally, the simulation result illustrates the performance of the proposed scheme with comparisons.