Improved iterative learning path-following control for USV via the potential-based DVS guidance

Abstract

Considering navigation scenarios in elaborate waters, the high-precision waypoints-based path-following problem of underactuated surface vessel (USV) is investigated by combining the iterative learning control (ILC) and the artificial potential field (APF) in this note. A potential-based dynamic virtual ship (DVS) guidance, considering the challenge of preventing collisions with irregular barriers, is designed with the path following module and the collision avoidance module. A virtual potential field is constructed in the guidance strategy to provide the desired heading signal In particular, the desired heading signal will force that to navigate to one secure location, where the USV approaches the barrier. On the basis of guidance, the iterative control algorithm is selected to design the controller of the system due to the advantages of high accuracy. The dynamic surface control (DSC) and the robust neural damping techniques are utilized to constraint the intrinsic problem of “explosion of complexity” in ILC. The merits of the method involve concise form and controllable precision. Through the Lyapunov criterion, the corresponding closed-loop system is with the semi-global uniformly ultimately bounded (SGUUB) stability. The simulation results are illustrated to verify the effectiveness of the proposed algorithm.