Neural Network Output-Feedback Distributed Formation Control for NMASs Under Communication Delays and Switching Network

Abstract

This article studies the neural network (NN) output-feedback distributed formation control problem of nonlinear multiagent systems (NMASs) under communication delays and jointly connected switching network. Since the communication between agents is affected by time-varying delay and some agents cannot access the leader's information under jointly connected switching network, a communication-delay-related distributed formation observer is designed to estimate the leader's information and simultaneously mitigate the effects of communication delays. NNs are adopted to identify unknown functions, and an NN state observer is established to reconstruct unmeasurable states. Then, based on the designed distributed formation observer and NN state observer, an NN output-feedback distributed formation control algorithm is proposed by the backstepping control theory. It is proven that the designed communication-delay-related distributed formation observer errors converge to zero exponentially. Meanwhile, the proposed distributed NN formation control approach ensures the NMAS is stable, and the formation tracking errors converge to a small neighborhood around zero. Finally, we apply the output-feedback distributed formation control scheme to unmanned surface vehicles (USVs), the simulation results verify its effectiveness.