Autonomous underwater vehicle precise motion control for target following with model uncertainty
Target following plays an important role in oceanic detection and target capturing for autonomous underwater vehicles. Due to the model nonlinearity and external disturbance, the dynamic model of a portable autonomous underwater vehicle was usually established with parameter uncertainties. In this a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2017-07-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/1729881417719808 |
| _version_ | 1818304447565004800 |
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| author | Huang Hai Zhang Guocheng Qing Hongde Zhou Zexing |
| author_facet | Huang Hai Zhang Guocheng Qing Hongde Zhou Zexing |
| author_sort | Huang Hai |
| collection | DOAJ |
| description | Target following plays an important role in oceanic detection and target capturing for autonomous underwater vehicles. Due to the model nonlinearity and external disturbance, the dynamic model of a portable autonomous underwater vehicle was usually established with parameter uncertainties. In this article, a petri-based recurrent type 2 fuzzy neural network has been built to approximate the unknown autonomous underwater vehicle dynamics. The type 2 fuzzy logic system has been applied to the network to improve the approximation accuracy for systematic nonlinearity, and the petri layer in the network can improve estimation speed and reduce energy consumption. A petri-based recurrent type 2 fuzzy neural network–based adaptive robust controller has been proposed for target tracking. In the offshore experiments, the proposed controller has not only realized stable position and pose control but also successfully followed mobile target on the surface. In the tank underwater experiments, the pipeline target has been successfully followed to further verify the controller performance. |
| first_indexed | 2024-12-13T06:10:51Z |
| format | Article |
| id | doaj.art-759aacd639a04ed4a5cd5c7ab420038e |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-13T06:10:51Z |
| publishDate | 2017-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-759aacd639a04ed4a5cd5c7ab420038e2022-12-21T23:57:05ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142017-07-011410.1177/1729881417719808Autonomous underwater vehicle precise motion control for target following with model uncertaintyHuang HaiZhang GuochengQing HongdeZhou ZexingTarget following plays an important role in oceanic detection and target capturing for autonomous underwater vehicles. Due to the model nonlinearity and external disturbance, the dynamic model of a portable autonomous underwater vehicle was usually established with parameter uncertainties. In this article, a petri-based recurrent type 2 fuzzy neural network has been built to approximate the unknown autonomous underwater vehicle dynamics. The type 2 fuzzy logic system has been applied to the network to improve the approximation accuracy for systematic nonlinearity, and the petri layer in the network can improve estimation speed and reduce energy consumption. A petri-based recurrent type 2 fuzzy neural network–based adaptive robust controller has been proposed for target tracking. In the offshore experiments, the proposed controller has not only realized stable position and pose control but also successfully followed mobile target on the surface. In the tank underwater experiments, the pipeline target has been successfully followed to further verify the controller performance.https://doi.org/10.1177/1729881417719808 |
| spellingShingle | Huang Hai Zhang Guocheng Qing Hongde Zhou Zexing Autonomous underwater vehicle precise motion control for target following with model uncertainty International Journal of Advanced Robotic Systems |
| title | Autonomous underwater vehicle precise motion control for target following with model uncertainty |
| title_full | Autonomous underwater vehicle precise motion control for target following with model uncertainty |
| title_fullStr | Autonomous underwater vehicle precise motion control for target following with model uncertainty |
| title_full_unstemmed | Autonomous underwater vehicle precise motion control for target following with model uncertainty |
| title_short | Autonomous underwater vehicle precise motion control for target following with model uncertainty |
| title_sort | autonomous underwater vehicle precise motion control for target following with model uncertainty |
| url | https://doi.org/10.1177/1729881417719808 |
| work_keys_str_mv | AT huanghai autonomousunderwatervehicleprecisemotioncontrolfortargetfollowingwithmodeluncertainty AT zhangguocheng autonomousunderwatervehicleprecisemotioncontrolfortargetfollowingwithmodeluncertainty AT qinghongde autonomousunderwatervehicleprecisemotioncontrolfortargetfollowingwithmodeluncertainty AT zhouzexing autonomousunderwatervehicleprecisemotioncontrolfortargetfollowingwithmodeluncertainty |