Robust super-twisting-based disturbance observer for autonomous underwater vehicles: Design, stability analysis, and real-time experiments

This paper proposes a new observation-based proportional–derivative control method for robust trajectory tracking of autonomous underwater vehicles (AUVs). The proposed control scheme is designed based on a new observation-based nonlinear model that captures the dynamics and uncertainties of the AUV’s behavior. The proposed control method is formulated in such a way that it can handle system nonlinearities and uncertainties, making it robust to external disturbances and model uncertainties. The effectiveness of the proposed control method is demonstrated through extensive real-time experiments in a real-world AUV trajectory tracking scenario. The obtained results show that the proposed control method outperforms other control methods in the literature regarding trajectory tracking accuracy, robustness, and disturbance rejection. Overall, the proposed observation-based proportional–derivative control method can significantly improve the trajectory tracking performance of AUVs in real-world applications.