Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
