Adaptive Backstepping Neural Network approach to ship course control

This paper describes an Adaptive Backstepping Neural Network (ABNN) method used for a ship course tracking control. The ship model is described by a third order nonlinear model whose parameters are unknown. The control design uses estimate values of unknown parameters of the system. Then, adaptive laws of the estimation of these values have been proposed. The stability of the controlled system has been ensured by the use of a Lyapunov function. Simulation results show the effectiveness of the proposed approach and the designed controller can be applied to the ship course tracking with good performances.