Adaptive Neural Networks Sliding Mode Backstepping Control for 3DOF Surface Ship with Uncertain Model

This paper proposes an adaptive sliding mode backstepping control algorithm for the tracking problem of uncertain ship model based on neural networks. The adaptive sliding mode backstepping controller (ASMBC) ensures that the surface ship tracks desired trajectory and resists disturbance. The unknown functions of ship-model are approximated by radial basis function networks. The stability analysis of closed ASMBC system will be given by the Lyapunov theorem. Simulation results on the PC are performed to demonstrate the effectiveness of the proposed algorithm.