The path-following control problem of an unmanned surface vehicle (USV) with unknown dynamics and unmeasured velocities is addressed in this paper. Main contributions are summarized as below: (1) considering that vehicle velocities are unmeasured directly, a finite-time velocity observer (FVO) is designed by utilizing available position information, which contributes to the path-following control and facilitates the implementation in practical engineering; (2) based on the traditional light-of-sight guidance, a heading-surge (HS) guidance scheme is proposed to guide USV surge velocity and heading angle, simultaneously; (3) in combination with wavelet neural network (WNN) and adaptive technique, unknown dynamics involving model uncertainties and environment interferences can be estimated accurately, thereby significantly enhancing system robustness. By the aid of the HS guidance based adaptive WNN controllers, all the error signals in the closed-loop system are uniformly ultimately bounded (UUB). Besides, simulation studies and comprehensive comparisons are conducted to demonstrate the satisfactory path-following performance and superiority of the proposed scheme.

中文翻译：

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未知动力学和未测量速度的无人水面车辆的路径跟踪控制

本文解决了具有未知动力学和未测量速度的无人水面车辆 (USV) 的路径跟踪控制问题。主要贡献总结如下：（1）考虑到车辆速度无法直接测量，利用可用的位置信息设计了有限时间速度观测器（FVO），这有助于路径跟踪控制并促进实际工程中的实现; (2)在传统视距制导的基础上，提出了航向-喘振(HS)制导方案，同时引导USV浪涌速度和航向角；(3)结合小波神经网络(WNN)和自适应技术，可以准确估计涉及模型不确定性和环境干扰的未知动态，从而显着增强系统鲁棒性。借助于基于 HS 制导的自适应 WNN 控制器，闭环系统中的所有误差信号都是一致最终有界（UUB）。此外，还进行了仿真研究和综合比较，以证明所提出的方案具有令人满意的路径跟随性能和优越性。