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Current Estimation and Path Following for an Autonomous Underwater Vehicle (AUV) by Using a High-gain Observer Based on an AUV Dynamic Model

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Abstract

A path following problem for autonomous underwater vehicles (AUVs) under a nonuniform current is presented in this paper. A dynamic model of an AUV in a nonuniform flow was adopted to develop a high-gain observer (HGO) for estimation of the three-dimensional current velocities along AUV trajectories. 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 current velocities were determined by calculating the differences between the measured absolute velocities of the vehicle and the estimated relative velocities of the vehicle estimated by the observer. The estimation error means of the HGO using the LMI have smaller values than the state observer with a gain matrix determined by the pole-placement approach. For the path following study, 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, an update law and a proportional and integral controller. Two cases of numerical simulations were conducted to verify the performance of the path following system combined with HGO for current compensation, and the results of both cases have shown that the AUV reached and converged to the desired path.

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Author information

Authors and Affiliations

  1. Australian Maritime College, University of Tasmania, Launceston, Tasmania, Australia

    Eonjoo Kim & Hung Nguyen

  2. School of Marine Sciences, Sun Yat-sen University, Zhuhai, Guangdong, China

    Shuangshuang Fan

  3. Memorial University of Newfoundland, St. John’s Newfoundland, Canada

    Neil Bose

Authors
  1. Eonjoo Kim
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  2. Shuangshuang Fan
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  3. Neil Bose
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  4. Hung Nguyen
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Corresponding author

Correspondence to Shuangshuang Fan.

Additional information

Recommended by Associate Editor Son-Cheol Yu under the direction of Editor-in-Chief Keum-Shik Hong.

This research was supported through an Australian Government Research Training Program Scholarship to the first author and undertaken thanks in part to funding from the Canada First Research Excellence Fund, through the Ocean Frontier Institute. Support was also received from Fisheries and Oceans Canada through the Multi-partner Oil Spill Research Initiative (MPRI) 1.03: Oil Spill Reconnaissance and Delineation through Robotic Autonomous Underwater Vehicle Technology in Open and Iced Waters.

Eonjoo Kim received her B.E. degree in marine and offshore engineering from the Australian Maritime College, University of Tasmania, Launceston, Australia in 2015, where she is currently working toward a Ph.D. degree in the College of Sciences and Engineering. Her research interests include the navigation and control of autonomous underwater vehicles.

Shuangshuang Fan received her B.E. degree in mechanical engineering from Shandong University, Jinan, China, in 2008 and a Ph.D. degree in mechatronic engineering from Zhejiang University, Hangzhou, China, in 2013. From October 2013 to October 2014, she was a Research Engineer with the Institute of Shanghai Aerospace Control Technology, Shanghai, China. She was with the Acoustic Signal Processing Lab, Zhejiang University, as a Postdoctoral Researcher from 2014.11 to 2017.4. From 2017.5 to 2019.7, she was a lecturer with the Australian Maritime College, University of Tasmania, Launceston, Australia. She is currently an associate professor at the School of Marine Sciences, Sun Yat-sen University, Zhuhai, China. She is also an Adjunct Professor at the Department of Ocean and Naval Architectural Engineering, Memorial University of Newfoundland, St. John’s, Canada. Her research interests include the navigation, control, and path planning of underwater vehicles in dynamic environments.

Neil Bose obtained his B.Sc. degree in Naval Architecture and Ocean Engineering from the University of Glasgow in 1978 and a Ph.D. degree, also from the University of Glasgow, in 1982. He was appointed Vice-President (Research) at Memorial University, Newfoundland and Labrador’s university in Canada, in November 2017. Prior to his appointment, he served as Principal of the Australian Maritime College (AMC), University of Tasmania since 2012. He joined AMC in May 2007 as the manager of the Australian Maritime Hydrodynamics Research Centre. He was also a professor of maritime hydrodynamics at the AMC. From 2009 to 2011, he was director of the AMC’s National Centre for Maritime Engineering and Hydrodynamics. Currently, he is also an Adjunct Professor at AMC. His research interests include marine propulsion, autonomous underwater vehicles, ocean environmental monitoring, ocean renewable energy, ice/propeller interaction and aspects of offshore design.

Hung Nguyen obtained his B.Sc. degree in Navigation from the Vietnam Maritime University in 1991, an M.E. degree in Marine Systems Engineering in 1998, and a Ph.D. degree in Marine Control Systems Engineering in 2001 from the Tokyo University of Marine Science and Technology. On completion of his Ph.D., he worked as a R&D engineer for a Japanese nuclear gauge manufacturer in Japan until August 2002. Since September 2002, Dr. Nguyen has been appointed as a lecturer in marine control engineering at the National Centre for Maritime Engineering and Hydrodynamics (NCMEH), the Australian Maritime College (AMC), University of Tasmania. He was the Graduate Research Coordinator at the NCMEH during 2014 and 2017. His research interests are in automatic control engineering, guidance, navigation and control of marine vehicles, modelling and simulation of marine and offshore systems including underwater vehicles as well as intelligent/smart marine vehicles.

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Kim, E., Fan, S., Bose, N. et al. Current Estimation and Path Following for an Autonomous Underwater Vehicle (AUV) by Using a High-gain Observer Based on an AUV Dynamic Model. Int. J. Control Autom. Syst. 19, 478–490 (2021). https://doi.org/10.1007/s12555-019-0673-5

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  • DOI: https://doi.org/10.1007/s12555-019-0673-5

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