The rolling and heeling experienced by a ship during turning will be more severe under the interference of winds and waves, which will seriously affect the navigation safety of the ship. The fin stabilizer is currently the best active anti-rolling device, which is usually used to reduce the roll of the ship during straight-line sailing. The purpose of this work is to study the use of fin stabilizers to reduce the rolling and heeling during ship turning, considering the non-linearity and uncertainty during the rotation. The 4 degrees of freedom (4-DOF) nonlinear motion model of a multi-purpose naval vessel is established. The forces and moments produced by fin stabilizers, rudders, propellers, and waves are also considered. The nonlinear control model of rotation and roll is derived and established. Given the non-linearity and uncertainty in the ship turning process, an L2-gain based robust adaptive control is proposed to control the fin stabilizers to reduce the turning heel and roll motion. The proof of the stability and the detailed design process of the controller are also given. Simulations are carried out to verify the effectiveness of the proposed control strategy. For comparison purposes, the simulation results under a well-tuned PID controller are also given. The simulation results show that the developed control strategy can effectively reduce the heel and roll during ship turns, and it has good robustness against uncertainty and internal and external interference.

Among the commonly used ship-stabilizing devices, the fin stabilizer is the most effective. Since the lift force of the conventional fin stabilizer is proportional to the square of the incoming flow velocity, it has a better anti-rolling effect at higher speeds but a poor anti-rolling effect at low speeds and even no effect at zero speed. A combination of modelling analysis, simulation, and a model ship experiment is used in this paper to study the zero-speed roll-reduction control problem of the fin stabilizer. A simulation model of the rolling motion of a polar expedition ship is established. The lift model of the fin stabilizer at zero speed is established using the theory of fluid mechanics. The proportional–integral–differential (PID) controller is selected to control the fin to achieve zero-speed roll reduction. To obtain a better anti-rolling control effect under variable sea conditions, a wavelet neural network (WNN)-based half-period prediction algorithm is adopted to update and adjust PID control parameters in real time. A simulation was carried out, and the effectiveness of the proposed predictive control algorithm is proved. A reduced-scale ship model was established to carry out the water tank experiment, and the results verify the theoretical analysis and simulation. The results also verify the effectiveness of the proposed control strategy.

In order to improve the accessibility of offshore wind O&M gangway in complex sea conditions, a control method for the controllable anti-rolling tank based on wavelet neural network period prediction is proposed in this paper. Firstly, a model of ship motion with a controllable passive anti-rolling tank was established. Then, the inverse kinematics of the gangway were carried out. In order to analyze the influence of the anti-rolling tank on the accessibility of the on-board gangway, an accessibility simulation of the gangway under different sea conditions was completed. Finally, a hardware-in-the-loop simulation of the active compensation gangway system was carried out. The simulation and test results show that the anti-rolling tank can effectively restrain the rolling motion of the ship and significantly improve the accessibility of the on-board gangway.