Neuroadaptive Inverse Optimal Resilient Formation Control for Nonlinear Multiagent Systems Under DoS Attacks

ABSTRACT This article investigates the adaptive neural network (NN) inverse optimal formation control issue for nonlinear multiagent systems (MASs) subject to denial‐of‐service (DoS) attacks. NNs are applied to model unknown nonlinear dynamics and an auxiliary system is established. Because the DoS attacks can disrupt the communication channels, the leader and the leader's high‐order derivatives are unknown, thus a distributed resilient observer is established to estimate them. With the help of the distributed resilient observer, a neuroadaptive inverse optimal resilient formation control method is proposed by the inverse optimal principle and backstepping control technology. It is proved that the formulated control scheme ensures that the controlled systems are stable, and the formation errors converge to zero's a small neighborhood. Moreover, the optimized control performance can be achieved. Eventually, the proposed neuroadaptive inverse optimized resilient formation control scheme is applied to marine surface vehicles, and the simulation results and comparisons indicate the effectiveness of the proposed inverse optimized formation control scheme.