A Time-Varying Lookahead Distance of ILOS Path Following for Unmanned Surface Vehicle

This paper is concerned with the path following control for an unmanned surface vessel subject to unknown dynamics and external disturbance. Firstly, an integral Line-of-Sight navigation strategy based on a fuzzy strategy to optimize lookahead distance to achieve faster convergence speed is proposed. Then a novel adaptive course control law based on trajectory linearization control technology is proposed, which is combined with the integral Line-of-Sight navigation strategy to form a complete unmanned surface vessel path following strategy. From the author's point of view, this is the first time that trajectory linearization control technology has been applied to the path following scheme by controlling the course. At the same time, in order to improve the robustness of the path following system, the unknown dynamics, external disturbance, and error in the system are compensated by neural network minimum learning parameter method with less computational complexity and a robust term, respectively. Furthermore, hyperbolic tangent function, Nussbaum function, and neural shunting model are introduced into the design of control law to solve the potential input saturation problem. Finally, the numerical simulation experiments of straight line and curve path following are given to prove the feasibility and universality of the whole set of path following scheme.