Ship Adaptive Track Keeping Control Based on Iterative Sliding Mode

The track control of underactuated ships, it is vulnerable to the influence of external factors such as wind and current. A nonlinear iterative sliding mode algorithm is proposed by using the iterative sliding mode and combining with the exponential incremental feedback, the asymptotic stability of the closed-loop system can be guaranteed without estimating external disturbances such as wind and current. By defining a kind of reinforcement learning signal with the ratio of ship angular rate to rudder angle, and using neural network to realize online adjustment of controller parameters, the controller's adaptability is improved, and the steering range and repetitive steering range are reduced. The nonlinear hydrodynamic model parameters of "YU LONG" wheel were used for MATLAB simulation. The results show that the controller is insensitive to external interference, system perturbation and strong robustness, compared with the non-adaptive iterative sliding mode, the chattering of rudder angle is obviously reduced.