Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance

Lei Wan,Lei Zhang,Jiangfeng Zeng,Hongde Qin,Jian Wang,Yueming Li

doi:10.1177/1729881419878071

Abstract

In this study, a new neural observer-based dynamic surface control scheme is proposed for the path following of underactuated unmanned surface vessels in the presence of input saturation and time-varying external disturbance. The dynamic surface control technique is augmented by a robust adaptive radial basis function neural network and a nonlinear neural disturbance observer. Radial basis function neural network is employed to deal with system uncertainties, and the nonlinear neural disturbance observer is developed to compensate for the unknown compound disturbance that contains the input saturation approximation error and the external disturbance. Moreover, the stringent known boundary requirement of the unknown disturbance constraint is eliminated with the proposed nonlinear neural disturbance observer. Meanwhile, to deal with the non-smooth saturation nonlinearity, a new parametric hyperbolic tangent function approximation model with arbitrary prescribed precision is constructed, which results in the transient performance improvement for the path following control system. Stability analysis shows that all the signals in the closed-loop system are guaranteed to be ultimately bounded. Comparative simulation results further demonstrate the effectiveness of the proposed control scheme.

Highlights

IntroductionUsing backstepping technique and Serret–Frenet frame, the path following control of autonomous underwater vehicles (AUVs) was studied by Lapierre et al.[8] and Zeng et al.[9] In Hu et al.,[10] the transient performance improvement for the path following of underactuated surface vessels was investigated based on a robust composite nonlinear feedback controller
In Zhang et al.,[13] a robust radial basis function neural network (RBFNN) waypoint-based path following control strategy was proposed for marine ships in the presence of multiobstacles
In Wang et al.,[14] an adaptive RBFNN controller was designed for cooperative path following of multiple marine surface vehicles (MSVs) subject to dynamical uncertainties

Summary

Introduction

Using backstepping technique and Serret–Frenet frame, the path following control of autonomous underwater vehicles (AUVs) was studied by Lapierre et al.[8] and Zeng et al.[9] In Hu et al.,[10] the transient performance improvement for the path following of underactuated surface vessels was investigated based on a robust composite nonlinear feedback controller. Note that in these literature, the parameters of the vehicles were assumed to be known,[8,9,10] or the parameters were unknown, while the nonlinearities were considered to be known.[6,7] it is difficult to obtain the mathematical model of the vessels accurately, and marine control applications are characterized by complex sea conditions. The dynamic surface control (DSC) technique with a first-order filtering of the synthetic input has been employed for tracking control of strict-feedback uncertain systems,[16] for formation control of autonomous surface vehicles,[17] and for path following control of underactuated ships.[18]

Methods

Discussion

Conclusion