Event-Triggered Fuzzy Adaptive Asymptotic Consensus Control of Nonlinear Multi-agent Systems Against FDI Attacks

This article considers the issue of resilient consensus control for nonlinear multi-agent systems in the case of false data injection (FDI) attacks on actuators and sensors. Compared with existing results, this article investigates a category of nonlinear strict-feedback systems, and real system states as well as real control inputs is not available under FDI attacks, which renders the controller design extremely complicated. To counteract the impact caused by sensor attacks, a fuzzy adaptive defense mechanism is constructed by the variable separation technique. Furthermore, actuator attacks are addressed by the Nussbaum function. In order to decrease the communication load on the control channel, a dynamic event-triggered strategy is introduced. Moreover, all signals of the closed-loop systems under the proposed control method are bounded, and output consensus with asymptotic convergence is realized in the case of FDI attacks. Finally, simulation studies are offered to assess the feasibility of the presented control method.