Title: An environmental disturbance observer framework for autonomous ships

Abstract: This paper proposes a robust disturbance observer framework for maritime autonomous surface ships considering model and measurement uncertainties. The core contribution lies in a nonlinear disturbance observer, reconstructing the forces on a ship impacted by the environment, such as wind, waves, and sea currents. For this purpose, mappings are found that describe global exponentially stable error dynamics by assuming slow changes of disturbances. With the stability theory of Lyapunov, it is proven that the error converges exponentially into a ball, even if the disturbances are highly dynamic. Since measurements are affected by noise and physical models can be erroneous, the measurements are filtered through an unscented Kalman filter and propagated through the proposed observer to deal with noisy measurements and inaccurate models. To investigate the capability of this observer framework, the environmental disturbances are simulated at different severity levels. The results depict the simulation of a severe, worst-case scenario consisting of highly dynamic disturbances, intense measurement noise, and an unreliable ship model. It can be seen that the observer framework accurately reconstructs the forces on a ship impacted by the environment despite using a low measurement sampling rate, an erroneous model, and uncertain measurements.