Adaptive region tracking control for underwater vehicles with large initial deviation and general uncertainty

Abstract

A region tracking control system is developed for underwater vehicles with large initial deviation and general uncertainty. The developed system is a nonlinear cascaded system, consisting of two subsystems in series. The fixed-gain controller of the first subsystem is designed to compensate for the region tracking error caused by the large initial deviation. In the second subsystem, the radial basis function neural network is adopted to approximate the general uncertainty along with the external disturbance and modelling uncertainty. According to the Lyapunov theory, the control law of the two subsystems and adaptive law of the second subsystem are derived to ensure the region tracking errors asymptotically converge to zero. The validity of the control system is verified by a series of comparisons on simulation results.