Design and experiments of an adaptive disturbance observer for tracking control of autonomous underwater vehicles

Underwater vehicles, controlled by human operators, often employ a simple internal control scheme, such as the Proportional Derivative (PD) controller. The choice of a PD controller is driven by its simplicity, ease of implementation, and acceptable reliability. However, this type of controller often exhibits limited robustness when facing parametric uncertainties (e.g., salinity variations) and external disturbances, such as sea waves. Motivated by these inherent limitations, we designed an adaptive disturbance observer using the Super-Twisting Algorithm. The primary objective of this observer is to enhance the robustness of the PD controller without compromising its simple and straightforward structure and minimizing the effort required for its tuning. Our proposed observer takes inspiration from the Extended State Observer (ESO) and is supported by a rigorous stability analysis using Lyapunov techniques. We also establish the stability of the closed-loop system involving the controller and observer. To showcase the effectiveness and reliability of our proposed method, we carried out a set of real-time experiments under various operating conditions.