Neural Sliding Mode Control for Tracking of Underactuated Ships Based on Backstepping

As for uncertain external interference and parameters, a self-adaptive neural sliding mode controller based on backstepping is designed for underactuated ships powered by wind, wave and flow. The chattering problem brought on by fixed switching coefficient of traditional sliding mode control (SMC) is restrained by using approaching-law SMC. And the neural network is utilized to reduce the dependence on plant model's parameters in approaching-law SMC. Results of a ship simulation indicate that the controller can effectively keep the given track and avoid the chattering phenomenon occurring in traditional sliding mode control and it can also control well under the external disturbance and parameter perturbation, which shows the controller strong robust.