ABSTRACT This paper investigates the leader–follower formation problem of underactuated surface vessels. Velocities of both leader and follower vessels are unavailable. Model uncertainties and ocean disturbances are also considered. By incorporating adaptive control, neural networks (NNs), the high-gain observer (HGO) and the minimal learning parameter (MLP) algorithm in the backstepping procedure, a novel adaptive output-feedback formation control scheme is developed. We show that formation errors can be guaranteed to be semiglobally uniformly ultimately bounded (SGUUB) with the proposed controller. Compared with existing methods, the formation can be achieved only with position and yaw angle of both leader and follower. Meanwhile, the developed scheme can enhance the robustness of the closed-loop system with less computational effort, where only two online parameters need to be tuned. Simulation and comparison results are provided to illustrate the effectiveness of theoretical results.

中文翻译：

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欠驱动水面舰艇的自适应输出反馈编队控制

摘要 本文研究了欠驱动水面舰艇的先导-跟随形成问题。领航船和跟随船的速度均不可用。模型的不确定性和海洋扰动也被考虑在内。通过在反步过程中结合自适应控制、神经网络 (NN)、高增益观测器 (HGO) 和最小学习参数 (MLP) 算法，开发了一种新颖的自适应输出反馈形成控制方案。我们表明，使用所提出的控制器，可以保证形成错误是半全局一致最终有界（SGUUB）。与现有方法相比，仅靠领航者和跟随者的位置和偏航角就可以实现编队。同时，所开发的方案可以以较少的计算量提高闭环系统的鲁棒性，其中只需要调整两个在线参数。提供了仿真和比较结果来说明理论结果的有效性。