This article presents a modified line-of-sight (LOS) guidance law and an adaptive neural network (NN) controller for underactuated marine vehicles in the presence of uncertainties and constraints. Unlike conventional LOS guidance, the proposed guidance law counteracts the drift caused by external disturbances to maintain zero cross-track error. Furthermore, an adaptive NN controller is designed using the barrier Lyapunov function (BLF) to deal with the system constraints and disturbances affecting unknown vehicle dynamics. The stability analysis of the adaptive controller guarantees the uniform ultimate boundedness of the closed-loop system. The proposed control strategy is verified in the simulation and experimental environment in the presence of external disturbances. Both simulation and experimental results confirm that the proposed modified LOS guidance law and adaptive NN controller guarantees asymptotic convergence to the desired path and maintains zero cross-track error despite environmental disturbances.

中文翻译：

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具有状态和输入约束的欠驱动海洋车辆的自适应神经网络控制的修正视距制导律


本文提出了一种改进的视距 (LOS) 制导律和自适应神经网络 (NN) 控制器，适用于存在不确定性和约束的欠驱动海洋车辆。与传统的LOS制导不同，所提出的制导律抵消了外部干扰引起的漂移，以保持零交叉航迹误差。此外，使用障碍李亚普诺夫函数（BLF）设计了自适应神经网络控制器来处理影响未知车辆动力学的系统约束和干扰。自适应控制器的稳定性分析保证了闭环系统的一致最终有界性。所提出的控制策略在存在外部干扰的仿真和实验环境中得到验证。仿真和实验结果均证实，所提出的改进的视距制导律和自适应神经网络控制器保证了渐近收敛到所需路径，并在环境干扰的情况下保持零交叉航迹误差。