Neuro‐Adaptive Optimal Cooperative Tracking Control for Nonlinear Multi‐Agent Systems Under Denial‐Of‐Service Attacks

This article studies the optimal cooperative tracking control problem of nonlinear multi‐agent systems (MASs) in the presence of unknown dynamics and denial‐of‐service (DoS) attacks. It is more challenging to achieve the desired optimized performance under DoS attacks, especially when neural networks are utilized to identify the unknown dynamics online. Considering two types of DoS attacks (connectivity‐maintained attacks and connectivity‐broken attacks), the article presents a novel defense control strategy consisting of a resilient distributed observer and a neuro‐adaptive optimal cooperative tracking controller. In specific, by introducing a label information algorithm, the resilient distributed observer for each follower agent is presented to reconstruct the leader's states under two types of DoS attacks. Subsequently, a neuro‐adaptive optimal cooperative tracking controller is proposed under an identifier‐critic‐actor architecture in the presence of DoS attacks. It is proven that the output of all follower agents can synchronize with that of the leader under DoS attacks, while the local performance indexes reach the Nash equilibrium simultaneously. Finally, the simulation results show the effectiveness of the presented optimal cooperative tracking control methodology.