This is the Way: Mitigating the Roll of an Autonomous Uncrewed Surface Vessel in Wavy Conditions Using Model Predictive Control

TL;DR

This paper develops a nonlinear model predictive control system for uncrewed surface vessels to reduce roll in wavy conditions, demonstrating a 39% reduction in average roll with potential for real-time planning in real-world scenarios.

Contribution

It introduces a novel NMPC approach that uses wave prediction to mitigate vessel roll, with a general tuning strategy and proof of concept for real-time control.

Findings

Reduced average roll by 39% in simulated conditions

Developed a wave-based prediction method for NMPC

Established a general tuning strategy for controllers

Abstract

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.