University of Tasmania
129544 - Autonomous underwater vehicle model-based high-gain observer for ocean.pdf (568.26 kB)

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

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conference contribution
posted on 2023-05-23, 13:48 authored by Kim, E, Fan, S, Neil Bose
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.


Publication title

Proceedings of the 2018 IEEE OES Autonomous Underwater Vehicle Symposium






Australian Maritime College



Place of publication

United States

Event title

2018 IEEE OES Autonomous Underwater Vehicle Symposium

Event Venue

Porto, Portugal

Date of Event (Start Date)


Date of Event (End Date)


Rights statement

Copyright 2018 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Intelligence, surveillance and space; Integrated systems