无人艇非线性航迹鲁棒自适应跟踪控制

Robust Adaptive Control for Nonlinear Path Tracking of Unmanned Surface Vehicles

针对欠驱动水面无人艇(USV)的非线性航迹跟踪控制问题,提出一种基于单调3次埃尔米特样条插值(CHSI)和神经网络的鲁棒自适应控制方法。采用CHSI方法对航路点进行拟合,得到光滑的非线性期望航迹,解决了传统线性航迹容易使USV出现的摇摆、曲折问题;引入SerretFrenet坐标系,并构建了自适应视线制导律,提高了收敛速度且减少了振荡;考虑USV模型的不确定性和环境干扰力影响,设计了简捷的鲁棒自适应神经网络控制器。稳定性分析结果证明了控制系统的收敛性;仿真实例验证了所提出的控制方法能够有效地改善USV航迹跟踪控制的精度和品质,并具有学习参数少、运算负载小的特点。

A robust adaptive control approach based on cubic Hermite spline interpolation( CHSI) and neural network is proposed for the path tracking of underactuated unmanned surface vehicles( USVs). A smooth nonlinear desired path is obtained by using CHSI method to fit the way-point,which solves the problem of swing and twist of USV caused by traditional linear path. Based on the Serret-Frenet frame,an adaptive line-of-sight( ALOS) guidance law is setablished to improve the rate of convergence and reduce the oscillation. Considering the influence of model uncertainties of USV and environmental disturbance,a concise robust adaptive neural network controller was developed. The proposed control strategy can effectively improve the accuracy and quality of path tracking control,and has the advantages of less learning parameters and computing load. The convergence of the system is proven through stability analysis,and the effectiveness of the proposed control scheme is verified by using the simulation examples.