Distributed Adaptive Target Capture Control for Marine Vehicles With Event-Triggered Communication Mechanism

This paper investigates the distributed adaptive target capture control problem for multiple marine vehicles with event-triggered communication. A novel tracking error-based dynamic threshold is integrated into the event-triggered mechanism to tackle the insufficient information exchange during large tracking errors. That achieves an appropriate tradeoff between communication efficiency and tracking accuracy. Only position information is selectively broadcasted at trigger instants, saving communication resources. An adaptive tuning parameter is designed to dynamically adjust the event-triggered virtual control laws based on real-time feedback. In addition, a robust adaptive disturbance observer based on neural networks (NNs) approximation is developed to tackle model uncertainties and ocean disturbances. By utilizing the switching reference technique, a concise virtual target-based capture strategy is proposed to ensure effective capture of the escaping target while reducing information dependency and path planning complexity. With the Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability of the closed-loop system is guaranteed, and the tracking errors converge to an arbitrarily small compact set without Zeno behavior. Experiment results demonstrate the effectiveness of the proposed algorithm.