## 1 Introduction
On the other hand, the method in [10] only adds the ocean currents in the kinematic model in terms of the relative surge and sway velocities, whereas the along-tracking error is omitted. The dynamics control system as the execution system of a USV is another crucial constituent in the path following scheme. In general, USVs do not have an independent actuator in their sway direction. This nonholonomic constraint and underactuated nature makes the control system design much more challenging [14]. To satisfy the successful execution of missions and achieve expected performance and robustness in the full range of work space from calm ocean environment to severe ocean environment along with inaccuracy system parameters, various nonlinear control methods have been proposed [15; 16; 17; 18; 19; 20; 21; 22]. In [15], external disturbances rejection method based on the reduced-order linear ESO is proposed. In [16], [PERSON] proposed a global path-tracking controller for underactuated ships under deterministic and stochastic loads where weak nonlinearly and strong Lyapunov design method is introduced and the estimations of disturbances are updated by projection algorithms. In [17; 18], nonlinear disturbance observers are utilized to estimate the ubiquitous external disturbances in the dynamics model of marine vehicles, where the disturbance estimation errors are proved to be UUB. In [19], a nonlinear adaptive PI sliding mode tracking controller is proposed to solve the environmental disturbance problems by relaxing the assumption of knowing the upper bound of the disturbance. In [20; 21], a novel adaptive switching-gain-based control method is proposed for a general uncertain Euler-Lagrange system, which is not only insensitive to the nature of uncertainties but can also alleviate the overestimation-underestimation problem. Moreover, intelligent control such as fuzzy and neural control has been applied to deal with the uncertainties and disturbances of underactuated marine surface ships. In [22], [PERSON] proposed an adaptive online constructive fuzzy controller where the fuzzy approximator is used to approximate the unknown disturbances. Besides, robust radial basis function neural network control laws and iterative neural network control laws are proposed in [23; 24], respectively, which are devoted to identifying and compensating the dynamical uncertainties and external disturbances. In addition, it should be noted that few of the aforementioned path following control schemes take into account input saturation. In fact, the practical constraint of actuators determined by the maximum forces and moments would degrade the performance of the control system or even make it unstable. Therefore, it is essential to implement the emulate of the constraint on the control laws design process for reliability and robustness. Motivated by the observations and considerations mentioned above, a finite-time currents observer based ILOS guidance is proposed to deal with unknown time-varying ocean currents, which is suitable for any desired parametric path with high accuracy control performance. Subsequently, adaptive control laws based on the RBFNN are designed, which solve input saturation with sophisticated auxiliary systems simultaneously. A robust adaptive controller is developed to address the path following problem, which is verified to be effective via numerical simulations. The main contributions of the paper are summarized as follows. 1. A finite-time currents observer based LOS guidance is presented to obtain the desired yaw angle and estimate the unknown time-varying ocean currents precisely, which significantly influences the performance of the control subsystem. 2. The RBF neural networks are incorporated into the kinetic controller to solve the uncertainties, which does not require any prior knowledge of the dynamics of the USV and disturbances, and the adaptive laws are designed to estimate the compound bounds of approximating errors and external time-varying disturbances. 3.