Distributed event-driven adaptive three-dimensional formation tracking of networked autonomous underwater vehicles with unknown nonlinearities

Abstract

This paper presents a distributed event-driven adaptive formation control strategy for networked uncertain nonlinear autonomous underwater vehicles (AUVs) in three-dimensional space. It is assumed that the leader information is only transmitted to a subset of AUV followers under a directed graph and the nonlinearities of the AUV dynamics are unknown. A distributed error transformation method is presented to address the distributed formation tracking problem of AUV followers in three-dimensional space. Then, a distributed event-driven adaptive control method using neural networks and stabilizing auxiliary signals is developed to ensure the stability of the event-driven closed-loop system and accomplish three-dimensional formation tracking in the Lyapunov stability sense. Additionally, it is shown that Zeno behavior does not occur in the resulting event-triggering strategy. A simulation demonstrates the effectiveness of the proposed theoretical methodology.