Intelligent ships at sea are influenced by environmental interference, and the influence of the uncertainty of model parameters leads to the problem of low ship motion control accuracy, so it is necessary to improve the resistance of the ship's control algorithm to such interference.

Based on an L1 adaptive control algorithm and Gaussian process regression (GPR) model, an L1 adaptive controller combined with a GPR model controller for underactuated ship path tracking control is proposed, and the control law is derived using the Lyapunov control function. The L1 adaptive controller is a new technique that considers both robustness and fast adaptivity. The closed-loop control system has proven to be consistently globally asymptotically stable, while the GPR model is used to model sudden disturbances and environmental disturbances during ship navigation, and achieve the rapid elimination of the effects of such disturbances in combination with the adaptive law.

The simulation results show that adding the GPR model reduces the average rudder amplitude by 14.9%, average absolute heading error by 23.2%, and maximum absolute heading error by 12.1%. The effects of environmental disturbances can be cancelled out faster and a stable state reached more rapidly than in cases without added disturbances.

The proposed L1-GPR adaptive controller can effectively resist various disturbances during navigation.

Aiming at the problem of the autonomous berthing control of tugboats, this study focuses on the application of a target tracking control strategy based on virtual leadership.

First, the autonomous berthing process of the tugboat is transformed into the target tracking control process of the virtual tugboat and actual tugboat. A kinematics model of the berthing system is then designed. Considering special environmental interference in the berthing scenario, the backstepping method and sliding mode control method are used to design an autonomous berthing controller for an azimuth stern drive tugboat. Three different sliding mode surfaces are provided and the stability is verified by the Lyapunov function. Finally, a simulation test is used to verify the control effect through the berthing trajectory, speed error and distance error.

The simulation results show that the designed tugboat autonomous berthing control strategy and controller have a good effect in the tugboat autonomous berthing scenario and good performance in the face of uncertain disturbances of the system.

The control strategy and berthing controller designed in this paper have good applicability and robustness. The autonomous berthing control of tugboats is realized from a new angle, providing a new direction for subsequent research on the berthing control of tugboats.

The navigation control system is the brain and center of an intelligent ship, and the safety and economy of the ship's navigation are directly determined by its control performance. Therefore, it is necessary to validate the ship intelligent navigation control system. This paper proposes a general verification platform, the variable stabilized ship, to simulate the sailing state of the target ship at different scales and with different hydrodynamic characteristics.

First, the structure of the variable stability ship is proposed on the basis of the model-following principle, and an analysis is made of the three degrees of freedom movement characteristics. The steady error between the variable stability ship and the target ship is determined by their position errors, and the variable stability controller is built on the basis of sliding mode control. Finally, Matlab simulations are carried which verify that the proposed method can maneuver the variable stability ship to follow the states of the target ship.

Simulation results show that the proposed method maneuver the variable stability ship to follow the states of the target ship.

The results of this study can provide references for the validation and verification of navigational control systems for intelligent ships.