Dynamic obstacle avoidance of unmanned ship based on event-triggered adaptive nonlinear model predictive control

• Published in: Ocean engineering Vol. 286; p. 115626
• Main Authors: Li, Shilong, Zhu, Yakun, Bai, Jianguo, Guo, Ge
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.10.2023
• Subjects: Adaptive model predictive control; Dynamic obstacle avoidance; Event-triggered; Trajectory tracking; Dynamic obstacle avoidance; Adaptive model predictive control; Trajectory tracking; Event-triggered
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2023.115626

This article studies trajectory tracking and dynamic obstacle avoidance problems of unmanned ships, and an event-triggered adaptive nonlinear model predictive control (EANMPC) method is constructed to solve the above problems. Firstly, a novel adaptive nonlinear model predictive control is used to track the trajectory of the unmanned ship. And then, an obstacle avoidance mechanism is formulated to deal with the condition of dynamic obstacles that appear during the unmanned ship trajectory tracking process. Secondly, an event-triggered mechanism is established to reduce the computational burden of the controller. Finally, several simulation results are provided for demonstrating the effectiveness and advantage of EANMPC. •A novel event-triggered mechanism for unmanned ship trajectory tracking is proposed.•A novel dynamic obstacle avoidance mechanism of the unmanned ship is designed.•A novel adaptive MPC method with event-triggered mechanism is proposed.•A method can reduce calculation times and adapt to parameters change is designed.