Autonomous Underwater Vehicle Model-Based High-Gain Observer for Ocean Current Estimation

Autor: Neil Bose, Shuangshuang Fan, Eonjoo Kim
Rok vydání: 2018
Předmět:
Zdroj: 2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV).
DOI: 10.1109/auv.2018.8729741
Popis: Autonomous Underwater Vehicles (AUVs) are being used for various ocean missions, and there are advantages in applying more accurate dynamic models for the vehicle control. In this paper, a high-gain observer (HGO) based on an AUV dynamics model in currents was presented to obtain three-dimensional water current velocities estimates. The current velocities were decided from the difference between the vehicle’s absolute velocities and the relative velocities estimated by the model-based HGO. The observer gain for the HGO was determined by solving the Linear Matrix Inequality (LMI) describing the estimate error dynamics. By adapding 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.
Databáze: OpenAIRE