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

Citation

Kim, E and Fan, S and Bose, N, Autonomous underwater vehicle model-based high-gain observer for ocean current estimation, Proceedings of the 2018 IEEE OES Autonomous Underwater Vehicle Symposium, 6-9 November 2018, Porto, Portugal, pp. 1-6. ISBN 9781728102535 (2018) [Refereed Conference Paper]


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Copyright Statement

Copyright 2018 IEEE

Official URL: http://dx.doi.org/10.1109/AUV.2018.8729741

Abstract

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.

Item Details

Item Type:Refereed Conference Paper
Keywords:autonomous underwater vehicle, control and estimation, path planning and navigation, high-gain observer, nonlinear observer, linear matrix Inequality
Research Division:Engineering
Research Group:Communications engineering
Research Field:Signal processing
Objective Division:Defence
Objective Group:Defence
Objective Field:Intelligence, surveillance and space
UTAS Author:Kim, E (Miss Eonjoo Kim)
UTAS Author:Fan, S (Dr Shuangshuang Fan)
UTAS Author:Bose, N (Professor Neil Bose)
ID Code:129544
Year Published:2018
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2018-12-05
Last Modified:2020-12-24
Downloads:23 View Download Statistics

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