Dynamic Event-Triggered Parallel Control of Under-Actuated Maritime Autonomous Surface Ships Subject to Ship-Shore Communications

This article investigates the digital-twin modeling and parallel control challenges of the under-actuated maritime autonomous surface ships (MASSs), aiming to achieve precise path-following tasks within the constraints of limited ship-shore communication network bandwidth resources. A safety-critical dynamic event-triggered parallel control architecture is proposed for the path-following control of an under-actuated MASS. Specifically, a dynamic event-triggered meta-learning extended state observer is designed to construct a digital-twin model, significantly reducing the sampling frequency of the actual MASS states. Next, utilizing control barrier functions designed based on surge and yaw velocities, optimal guidance signals are obtained that satisfy velocity and safety constraints, ensuring effective collision avoidance of all obstacles. Finally, a dynamic event-triggered parallel path-following control law is proposed based on the digital-twin model and the optimal guidance signals, ensuring accurate path-following performance without being affected by the changes in the diverse sea environments. By utilizing cascade system theory and Zeno analysis, it is proven that the closed-loop system exhibits input-to-state stability, and the proposed dynamic event-triggered parallel path-following control method does not cause Zeno behavior. Simulation results demonstrate that the proposed method can achieve the path following and ship-shore state synchronization with less network bandwidth resources.