Disturbance Estimation for Unmanned Surface Vehicles using a Nonlinear Disturbance Observer
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Abstract
An Unmanned Surface Vehicle (USV) is a maritime transportation system designed to operate autonomously. However, in complex marine environments, the vessel is subjected to external disturbances such as wind, ocean currents, and waves that can affect the stability and robustness of its motion control system. This study aims to estimate these disturbances in real time using a Nonlinear Disturbance Observer (NDO) and to utilize the estimated disturbances to update the predictive model in a Disturbance Compensating–Nonlinear Model Predictive Control (DC-NMPC) framework. The estimation considers two types of disturbances: constant disturbances representing steady wind and current forces, and periodic disturbances representing wave effects modeled as sinusoidal functions. These disturbances affect the sway velocity (v) and yaw velocity (r) of the vessel. Simulation results show that the NDO is capable of reconstructing the actual disturbances with bounded and consistent estimation errors. This is indicated by RMSE values of 0.0070 for d1 and 0.0605 for d2 under the tested disturbance scenario. The estimation performance remains consistent under variations of the observer gain matrix, indicating observer stability. Increasing the gain improves the estimation response speed but slightly increases the error, revealing a trade-off between responsiveness and estimation accuracy. Furthermore, the observer is able to track time-varying sinusoidal disturbances, demonstrating robustness against dynamic environmental disturbances. These results indicate that
NDO-based disturbance estimation can enhance the robustness of USV motion control under environmental disturbances.
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References
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