2024/08/27 by Daniel L. Jenkins, Jenkins, Daniel L., Joshua A. Marshall +1
Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #Hydraulic and Pneumatic Systems #Mechanical Failure Analysis and Simulation #Oil and Gas Production Techniques #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2408.15349
openalex publication_date 2024/08/27 · openalex created_date 2024/09/22 · openalex updated_date 2026/07/28
Though larger vessels may be well-equipped to deal with wavy conditions, smaller vessels are often more susceptible to disturbances. This paper explores the development of a nonlinear model predictive control (NMPC) system for Uncrewed Surface Vessels (USVs) in wavy conditions to minimize average roll. The NMPC is based on a prediction method that uses information about the vessel's dynamics and an assumed wave model. This method is able to mitigate the roll of an under-actuated USV in a variety of conditions by adjusting the weights of the cost function. The results show a reduction of 39% of average roll with a tuned controller in conditions with 1.75-metre sinusoidal waves. A general and intuitive tuning strategy is established. This preliminary work is a proof of concept which sets the stage for the leveraging of wave prediction methodologies to perform planning and control in real time for USVs in real-world scenarios and field trials.