Adaptive path following control for autonomous surface vehicles towed by a single tugboat with output constraints.

This paper proposes an adaptive fixed-time path-following control scheme for autonomous tugboats towing vessels, addressing both performance and feasibility constraints. To establish a clear path relationship, the kinematic models of the tugboat and the towed vessel are decoupled, allowing coordinated control through the tugboat's propulsion system and towline dynamics. Building on this foundation, a barrier Lyapunov function combined with an adaptive backstepping approach is employed to design a controller that ensures high navigation accuracy while meeting output constraints. To achieve seamless coordination, a consensus-based dynamic controller is developed, enabling velocity and heading synchronization between the tugboat and the towed vessel. Furthermore, a fixed-time convergence algorithm is incorporated, guaranteeing system stability and error convergence within a predefined time frame. To enhance robustness against nonlinear uncertainties and external disturbances, radial basis neural networks and adaptive robust terms are integrated into the control framework. Finally, simulation results validate the effectiveness of the proposed approach, demonstrating precise path-following performance and reliable error convergence under complex operational conditions.