Distributed dynamic event-triggered flocking control for multiple unmanned surface vehicles

This paper proposes a distributed dynamic event-triggered control that addresses the flocking control problem with a virtual leader for multiple unmanned surface vehicle (USV) systems. Unlike existing flocking algorithms, which often result in the formation of quasi alpha-lattice structures, the proposed approach combines artificial potential functions (APF), directionally consistent potential functions (DCPF), and a navigation feedback term to form an alpha-lattice. A novel artificial potential function is developed to facilitate flocking and maintain a safe distance between USVs to avoid collisions. Additionally, a dynamic event-triggered mechanism, initially employed in flocking control, is introduced to reduce communication among USVs. Furthermore, it is demonstrated that Zeno behavior does not occur. The algorithm employs Radial Basis Function Neural Networks (RBFNNs) and adaptive algorithms to dynamically estimate and compensate for parameter uncertainties and external disturbances. Finally, the effectiveness and robustness of the proposed algorithm are verified through numerical simulation.