Practical identification approach for the actuation dynamics of autonomous surface vehicles with minimal instrumentation

Abstract

A practical method for identifying the propeller model and inertia matrix of a marine Autonomous Surface Vehicle (ASV) is proposed in this work. Special attention is paid to limiting the instrumentation requirements. Based on a generic grey-box dynamic modelling addressing the considered catamaran-shaped ASV architecture, the static/dynamic behaviour of both propellers and the vessel dynamic are jointly estimated using the sole measurements of position, heading, and propellers pulse width modulation (PWM) signals. No accelerometer is required. Two distinct grey-box configurations involving either a static polynomial or a dynamic modelling of each propeller are proposed and compared. The resulting ASV identification methodology is shown to provide insight into the whole vessel inertial characteristics, which are key enablers in the development of autonomous navigation and control systems. Model validation was performed using data collected from the reported experiments. Model prediction errors related to both linear velocities and yaw rate are evaluated and compared based on given metrics. The results underscore the robustness and accuracy of the identified models in capturing the essential dynamics of the ASV, with a determination coefficient that consistently exceeds 0.94 for all estimated velocities.