Adaptive Fault-Tolerant Consensus Tracking Control of Stochastic High-Order MASs Under FDI Attacks

This article studies the adaptive fault-tolerant consensus tracking control problem for a class of stochastic nonlinear high-order multiagent systems (MASs) under stochastic false data injection (FDI) attacks. Based on the fuzzy logic systems and backstepping design technique, a novel adaptive fuzzy fault-tolerant consensus tracking control strategy is proposed to guarantee that the closed-loop stochastic high-order MASs are semiglobally stable in probability via stochastic Lyapunov stability theory and It
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lemma. In order to relieve the communication pressure of MASs, a novel high-order dynamic event-triggered mechanism (DETM) based on user-set parameters is developed. Compared with the traditional event-triggered mechanism, this DETM has larger triggering time intervals, effectively reduces communication frequency, and has greater flexibility in balancing system performance and communication bandwidth resource constraints. Finally, the actual simulation and comparative simulation are given to verify the effectiveness and superiority of the proposed scheme.