Autonomous underwater vehicle model-based high-gain observer for ocean current estimation

Autonomous Underwater Vehicles (AUVs) are being used as specialised tools for various ocean missions, and there are advantages in applying more accurate dynamic models for control. In this study, a high-gain observer (HGO) based on an AUV dynamics model is presented to estimate three dimensional water current velocities. The water current velocities were determined by calculating the differences between the vehicle’s absolute velocities and the relative velocities estimated by the model-based HGO. The HGO was chosen as a nonlinear algorithm to estimate the vehicle’s relative velocities. The Lyapunov stability of the estimation error dynamics was investigated. The observer gain was computed by solving the Linear Matrix Inequality (LMI) which represented the error dynamics. By utilising the AUV model-based HGO, the vehicle’s relative velocity was estimated, then the current velocity vector was subsequently calculated. AUV numerical simulations and field test results were used to confirm the effectiveness of the proposed HGO, and the improvements over previous solutions.