High-precision Path-following Control for Underactuated Vessels via the Improved Dynamic Virtual Ship Guidance

• Published in: 2022 IEEE International Conference on Unmanned Systems (ICUS) pp. 1203 - 1208
• Main Authors: Shang, Xiaoyong, Zhang, Guoqing, Zhang, Xianku
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.10.2022
• Subjects: Artificial Potential Field; Computational modeling; Heuristic algorithms; Iterative algorithms; Iterative Learning Control; Marine vehicles; Neural networks; path-following control; Stability analysis; underactuated vessels; Voltage control
• ISSN: 2771-7372
• DOI: 10.1109/ICUS55513.2022.9986515

This paper investigates the problem of high-precision path-following and automatic obstacle avoidance for underactuated vessels. An artificial potential field (APF) is introduced into the dynamic virtual ship (DVS) guidance to propose a new guidance scheme to assure the rationality of the obstacle avoidance mechanism, which can automatically plan the planned route according to the route point and use the planned route as the gravitational source. In terms of control, an improved Iterative Learning Control (ILC) algorithm is designed. For engineering implementation, backstepping, neural networks, and dynamic surface control (DSC) techniques are used to reduce the computational effort of the algorithm. The derived controller is with the advantages of high accuracy, low computational effort, and is easy to engineering implementation. The theoretical stability of the closed loop control system was proofed by the Lyapunov theorem. Finally, the feasibility of the scheme is verified by simulation experiments.