This paper investigates the robust course control for marine surface vehicles (MSVs) by using reinforcement learning and a dynamic event-triggered mechanism under rudder faults. A fault-tolerant optimized tracking control scheme is designed based on reinforcement learning. Firstly, a general actuator fault model is established. Secondly, internal and external disturbances as well as fault dynamics are aggregated into lumped uncertainties, and a fault observer is constructed to estimate and compensate the lumped uncertainty term. Then, a tracking cost function for the MSV system is constructed, and a reinforcement learning framework with a single critic network is used to approximate the value function and generate a learning-based compensation input. Finally, a dynamic event-triggered mechanism is implemented between the control layer and the execution layer to reduce the triggering frequency of actuators. Lyapunov stability theory is utilized to prove that all signals within the closed-loop system are uniformly ultimately bounded. Simulation results verify that the proposed control scheme achieves favorable overall performance.

This paper formulates a self-organized dynamic fencing problem for multiple AUVs under finite target-sensing range and bounded nonuniform acoustic communication delays. Here, self-organization means that the fence is generated by local interactions without assigning fixed angular slots, virtual leaders, or persistent vehicle roles. A minimal observer-assisted attraction-repulsion fencing controller is proposed for AUV implementation, comprising target-AUV radial attraction–repulsion, AUV–AUV distance attraction–repulsion computed from timestamp-aligned delayed neighbor states, a state-only target-motion observer, and a label-free bearing-coverage repulsion that acts only on oversized target-centered angular gaps. To address acoustic delay without delaying physical execution, each AUV stores its own state history and evaluates pairwise relative geometry at the timestamp carried by the received neighbor packet. The resulting command is applied at the current time. The analysis shows that timestamp alignment converts acoustic delay into a bounded geometric perturbation and establishes collision avoidance, radial confinement, angular-gap contraction, target tracking, and packet-range preservation on a locally order-consistent regular fencing interval. The theorem does not claim global entry from arbitrary non-enclosing configurations. Numerical simulations, including a five-degree-of-freedom ocean-current robustness test without current feedforward compensation and an evasive-target stress test with four rapid finite-acceleration turns, demonstrate self-organized entry and maintenance of compact convex-hull fencing in the tested cases.