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



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Abstract
Autonomous Underwater Vehicles (AUVs) arebeing used as specialised tools for various ocean missions, andthere are advantages in applying more accurate dynamic modelsfor control. In this study, a high-gain observer (HGO) based onan AUV dynamics model is presented to estimate three dimensionalwater current velocities. The water current velocitieswere determined by calculating the differences between thevehicle’s absolute velocities and the relative velocities estimatedby the model-based HGO. The HGO was chosen as a nonlinearalgorithm to estimate the vehicle’s relative velocities. TheLyapunov stability of the estimation error dynamics wasinvestigated. The observer gain was computed by solving theLinear Matrix Inequality (LMI) which represented the errordynamics. By utilising the AUV model-based HGO, the vehicle’srelative velocity was estimated, then the current velocity vectorwas subsequently calculated. AUV numerical simulations andfield test results were used to confirm the effectiveness of theproposed HGO, and the improvements over previous solutions.
Item Type: | Conference Publication |
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Authors/Creators: | Kim, E and Fan, S and Bose, N |
Keywords: | autonomous underwater vehicle, control and estimation, path planning and navigation, high-gain observer, nonlinear observer, linear matrix Inequality |
Journal or Publication Title: | Proceedings of the 2018 IEEE OES Autonomous Underwater Vehicle Symposium |
Publisher: | IEEE |
DOI / ID Number: | https://doi.org/10.1109/AUV.2018.8729741 |
Copyright Information: | Copyright 2018 IEEE |
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