Event‐Triggered Adaptive Fuzzy Secure Consensus Control of Nonlinear Multi‐Agent Systems Under Dos Attacks

ABSTRACT Since denial‐of‐service (DoS) attacks lead to the instability of multi‐agent systems (MASs) and the event‐triggered mechanism can reduce the communication resources, studying the event‐triggered adaptive fuzzy secure consensus control (SCC) problem for nonlinear multi‐agent systems (NMASs) under DoS attacks is a very important topic. However, the existing adaptive secure control approaches assume that the leader signal of the system is known under DoS attacks. Furthermore, the existing event‐triggered adaptive secure control works only focus on the event‐triggered mechanism for the controller‐to‐actuator channel of NMASs under DoS attacks, and the existing dual‐channel event‐triggered adaptive control schemes for both the sensor‐to‐controller channel and controller‐to‐actuator channel do not consider DoS attacks. Therefore, this article studies the dual‐channel event‐triggered adaptive fuzzy SCC issue for NMASs under DoS attacks. Since the communication topology of NMASs is disrupted by DoS attacks, the leader signal and its high‐order derivatives are unavailable, a distributed resilient observer is designed to estimate them. A dual‐channel event‐triggered mechanism for the sensor‐to‐controller and controller‐to‐actuator channels is designed. Based on this event‐triggered mechanism, and by introducing a high‐order chain‐like filter into the backstepping control design process to solve the nondifferentiable problem of the virtual controller caused by the triggered output signals, an event‐triggered adaptive fuzzy SCC method is developed by fuzzy logic systems (FLSs). The developed SCC method ensures that the NMASs are stable, and the consensus tracking errors converge to a small neighborhood around zero. Furthermore, it saves the dual‐channel communication resources. Finally, we apply the developed event‐triggered SCC approach to control multiple Euler–Lagrangian systems, and the simulation and comparison results verify its effectiveness.