Neural Network-Based Adaptive Impulsive Control Strategy for Leader-Following Consensus in Uncertain Multiagent Systems

This paper investigates a Neural Network-based (NN-based) adaptive impulsive control approach to address the leader-following consensus problem in uncertain multiagent systems under deception attacks. A novel adaptive impulsive control strategy is developed to mitigate the impact of uncertain nonlinearities and deception attacks. This strategy not only ensures faster convergence but also reduces the consumption of communication resources. Simulation examples are provided to verify the effectiveness of the proposed adaptive impulsive control method.