Adaptive sliding mode heading control for autonomous underwater vehicle including actuator dynamics

An adaptive sliding mode heading control approach is proposed for autonomous underwater vehicle (AUV) including the dynamics of rudder in this paper. By the analysis of the driving principle of the rudder, a three-order state equation for AUV heading control system is established, in which the system input is the control voltage of the DC motor. For the problem of the modeling uncertainties, an adaptive identification method based on radial basis function (RBF) neural networks is proposed. Based on the backstepping method, the sliding mode control law are designed. The convergence of the control system is proved by Lyapunov stability theory. Finally, the proposed method is verified by comparison simulation.