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Path following for an autonomous underwater vehicle (AUV) by using a high-gain observer based on an AUV dynamic model

Citation

Kim, E and Fan, S and Bose, N and Nguyen, HD, Path following for an autonomous underwater vehicle (AUV) by using a high-gain observer based on an AUV dynamic model, IFAC-PapersOnLine, 52 (21): Proceedings of the 12th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles (CAMS 2019), 18-20 September 2019, Daejeon, South Korea, pp. 218-223. ISSN 2405-8963 (2019) [Refereed Conference Paper]


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Copyright Statement

Copyright 2019 IFAC (International Federation of Automatic Control)

DOI: doi:10.1016/j.ifacol.2019.12.310

Abstract

In this paper a curved path following problem for autonomous underwater vehicles (AUVs) moving in a nonuniform ocean current is presented. A high-gain observer (HGO) based on an AUV dynamic model was used to estimate three dimensional current velocities. The current velocities were determined by calculating the differences between the vehicle’s absolute velocities and the vehicle’s relative velocities estimated by the observer. The HGO was chosen as a nonlinear estimation algorithm, and the observer gain was computed by solving a Linear Matrix Inequality (LMI) which represented the estimation error dynamics. The desired curved path was represented by using a Serret-Frenet frame which propagated along the curve. The path-following system includes a guidance law, un update law and a proportional and integral controller. Two cases of numerical simulations were conducted to verify the performance of the path following system.

Item Details

Item Type:Refereed Conference Paper
Keywords:autonomous underwater vehicles, path following, high-gain observer, ocean current
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Special vehicles
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)
UTAS Author:Nguyen, HD (Dr Hung Nguyen)
ID Code:139182
Year Published:2019
Deposited By:Mathematics
Deposited On:2020-05-29
Last Modified:2020-06-16
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