Window Impulsive Consensus of Time‐Varying Multi‐Agent Systems Under Deception Attacks on Time Scales

ABSTRACT This paper addresses the consensus problem for time‐varying multi‐agent systems (MASs) under deception attacks on time scales. A novel hybrid control strategy is proposed, integrating sampled‐data feedback with time‐varying window impulsive control, which eliminates the conventional requirement of preset fixed impulsive instants. To characterize deception attacks on transmission channels, Bernoulli‐distributed random variables are introduced to model the occurrence and probability of attacks. Moreover, average parameters related to impulsive gains and time‐varying window boundaries are incorporated into the design. Based on time‐scale theory and Lyapunov stability analysis, sufficient conditions are derived for achieving both leader‐following consensus and dynamic average consensus. These conditions, which depend on the average parameters, not only relax the constraints on impulsive gains but also reduce the required frequency of impulsive control inputs. The effectiveness of the proposed control scheme is validated through numerical simulations.