Tracking Control of Podded Propulsion Unmanned Surface Vehicle with Unknown Dynamics and Disturbance Under Input Saturation

Abstract

This paper addresses two interrelated problems concerning the tracking control of podded propulsion unmanned surface vehicle (USV), namely, the modeling of podded propulsion USV, and trajectory tracking controller design. Based on the force analysis, the separation model of podded propulsion USV is established. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network minimum parameter learning method, neural shunting model and auxiliary dynamic system without the exact information of hydrodynamic damping structure and the sea disturbances. Using Lyapunov stability analysis theory, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of podded propulsion USV is demonstrated; then, neural shunting model and neural network minimum parameter learning method are introduced to cope with the problem of "explosion of complexity" and uncertainty factors, respectively; third, auxiliary dynamic system is introduced into controller design to reduce the risk of actuator saturation. Taking into account the above practical problems is helpful to engineering implementation in the marine practice. Finally, numerical simulation has been given to demonstrate the effectiveness of the proposed scheme.