Mean-Square Bounded Consensus of Nonlinear Multi-Agent Systems with Time-Varying Delays via Impulsive Control Under Dual-Channel Stochastic Switching Deception Attacks

This paper presents a novel dual-channel stochastic deceptive attack scheme, designed for multi-agent systems (MASs) utilizing directional network structures. The scheme compromises both sensor-controller (S-C) and controller-actuator (C-A) channels with distinct tampered signals during variable impulsive control intervals. To counter these attacks, an adaptive secure impulsive coordination strategy has been developed for a kind of non-linear Multi-Agent Systems with time-varying and dynamic switching capabilities. In this model, the stochastic selection of compromised channels obeys Bernoulli distributions. Based on Lyapunov's stability theorem, methods of matrix analysis, and linear matrix inequality techniques, adequate conditions are established to guarantee consensus in the mean-square sense with bounded errors for the system. Our key contributions include: (i) Novel criteria guaranteeing error-bounded consensus with explicit residual disagreement bounds; (ii) The first framework integrating dual-channel stochastic attacks with adaptive impulsive defense and time-varying delay functions; (iii) Analytical quantification of attack impacts on consensus precision. Two simulation cases are given to address the effectiveness of the derived results.