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This paper shows solicitude for the path following control issues of underactuated unmanned surface vehicles subject to unknown external disturbances, deviation of vessel model parameters and actuator saturation. Initially, an improved adaptive integral line-of-sight (IALOS) guidance law is introduced to estimate the sideslip angle, which helps to promote the precision of path following. Furthermore, a finite-time convergent disturbance observer is utilized to size up time-varying disturbances and the single-parameter neural network strategy is utilized to reduce the impact of model deviation. Meanwhile, by introducing a finite-time auxiliary dynamic system to improve the impact of actuator saturation (input saturation), the higher-order tracking differentiator (TDS) is introduced into the backstepping controller for reducing the number of derivations. It is shown that all error signals of the control system, employing Lyapunov stability theory, are uniformly ultimately bounded. Finally, the validity of the put forward scheme is validated by numerical simulations.

Robust Adaptive Path Following Control Strategy for Underactuated Unmanned Surface Vehicles with Model Deviation and Actuator Saturation