Command filter based adaptive neural trajectory tracking control of an underactuated underwater vehicle in three-dimensional space

This study focuses on the three-dimensional trajectory tracking control problem of an underactuated underwater vehicle subject to parameter uncertainties and external disturbances. Firstly, the five degrees freedom dynamic model of an underactuated AUV is constructed, and the trajectory tracking error dynamic model is established. Secondly, a nonlinear robust control scheme is presented based on the command filtered backstepping method, which not only greatly reduces the computational complexities in the traditional backstepping approach, but also filters out the high frequency measurement noise in the trajectory tracking. Moreover, the neural networks and adaptive control techniques are employed to estimate and compensate the effect of parameter uncertainties in the control system. Thirdly, in order to guarantee the approximation precision between the virtual control vaules and the filtered signals, a Lyapunov-based filtered error compensation loop is designed, and an anti-windup design is also developed to deal with the problem of integral saturation in control input signals. After that, the stability of the control scheme proposed in this paper is proved in the sense of Lyapunov stability theory. Finally, comparative simulations were carried out to illustrate the effectiveness and good robustness of the proposed tracking controller.