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船舶的自适应神经网络控制修正的视线制导律

本文针对存在不确定性和约束的情况，针对欠驱动的海上航行器提出了一种改进的视线（LOS）制导律和自适应神经网络（NN）控制器。与常规的LOS制导不同，拟议的制导律抵消了由外部干扰引起的漂移，以保持零跨轨误差。此外，使用障碍Lyapunov函数（BLF）设计了一种自适应NN控制器，以处理系统约束和影响未知车辆动态的干扰。自适应控制器的稳定性分析确保了闭环系统的一致极限极限。在存在外部干扰的情况下，在仿真和实验环境中验证了所提出的控制策略。