Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV

The hydrodynamic coefficients of underwater robots can be used to evaluate their maneuverability and motion stability and to design motion controllers, thereby reducing experimental time and costs. In this paper, an Autonomous Underwater Vehicle (AUV) with a negative-lift profile is designed. The sp...

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Main Authors: Lunyang Lin, Yuxiang Chen, Hong Xiong, Chunliang Yu, Hong Zhu, Yiyang Xing, Guodong Zheng
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/13/2/310
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author Lunyang Lin
Yuxiang Chen
Hong Xiong
Chunliang Yu
Hong Zhu
Yiyang Xing
Guodong Zheng
author_facet Lunyang Lin
Yuxiang Chen
Hong Xiong
Chunliang Yu
Hong Zhu
Yiyang Xing
Guodong Zheng
author_sort Lunyang Lin
collection DOAJ
description The hydrodynamic coefficients of underwater robots can be used to evaluate their maneuverability and motion stability and to design motion controllers, thereby reducing experimental time and costs. In this paper, an Autonomous Underwater Vehicle (AUV) with a negative-lift profile is designed. The spatially constrained motion method, combined with neural networks, is utilized to identify all the hydrodynamic coefficients in the standard hydrodynamic equations of the AUV. Subsequently, based on the goodness-of-fit, the significance of the hydrodynamic coefficients is evaluated to yield a simplified hydrodynamic equation. Given the cost constraints, it was not feasible to obtain precise experimental data on hydrodynamic coefficients to validate the accuracy of the CFD calculation method. Therefore, the hydrodynamic coefficients were used to construct a dynamic model for the AUV, and an MPC controller was designed based on this model. Finally, simulations and pool tests were conducted on the AUV, and a comparative analysis of the simulation results with the pool test results revealed that although there were certain errors in the calculation of the hydrodynamic coefficients, the controller constructed within this margin of error was still capable of effectively controlling the AUV. This fully demonstrates the feasibility and applicability of using CFD methods to calculate hydrodynamic coefficients and establishing model predictive control methods based on these coefficients in practical applications.
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institution DOAJ
issn 2077-1312
language English
publishDate 2025-02-01
publisher MDPI AG
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series Journal of Marine Science and Engineering
spelling doaj-art-e62de7124644401a9b3be99c9686afa22025-08-20T03:11:21ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-02-0113231010.3390/jmse13020310Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUVLunyang Lin0Yuxiang Chen1Hong Xiong2Chunliang Yu3Hong Zhu4Yiyang Xing5Guodong Zheng6Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaThe hydrodynamic coefficients of underwater robots can be used to evaluate their maneuverability and motion stability and to design motion controllers, thereby reducing experimental time and costs. In this paper, an Autonomous Underwater Vehicle (AUV) with a negative-lift profile is designed. The spatially constrained motion method, combined with neural networks, is utilized to identify all the hydrodynamic coefficients in the standard hydrodynamic equations of the AUV. Subsequently, based on the goodness-of-fit, the significance of the hydrodynamic coefficients is evaluated to yield a simplified hydrodynamic equation. Given the cost constraints, it was not feasible to obtain precise experimental data on hydrodynamic coefficients to validate the accuracy of the CFD calculation method. Therefore, the hydrodynamic coefficients were used to construct a dynamic model for the AUV, and an MPC controller was designed based on this model. Finally, simulations and pool tests were conducted on the AUV, and a comparative analysis of the simulation results with the pool test results revealed that although there were certain errors in the calculation of the hydrodynamic coefficients, the controller constructed within this margin of error was still capable of effectively controlling the AUV. This fully demonstrates the feasibility and applicability of using CFD methods to calculate hydrodynamic coefficients and establishing model predictive control methods based on these coefficients in practical applications.https://www.mdpi.com/2077-1312/13/2/310negative-liftcomputational fluid dynamicsspatial captive motionneural networksmodel predictive control
spellingShingle Lunyang Lin
Yuxiang Chen
Hong Xiong
Chunliang Yu
Hong Zhu
Yiyang Xing
Guodong Zheng
Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV
Journal of Marine Science and Engineering
negative-lift
computational fluid dynamics
spatial captive motion
neural networks
model predictive control
title Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV
title_full Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV
title_fullStr Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV
title_full_unstemmed Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV
title_short Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV
title_sort hydrodynamics model identification and model based control application of a new type of auv
topic negative-lift
computational fluid dynamics
spatial captive motion
neural networks
model predictive control
url https://www.mdpi.com/2077-1312/13/2/310
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AT chunliangyu hydrodynamicsmodelidentificationandmodelbasedcontrolapplicationofanewtypeofauv
AT hongzhu hydrodynamicsmodelidentificationandmodelbasedcontrolapplicationofanewtypeofauv
AT yiyangxing hydrodynamicsmodelidentificationandmodelbasedcontrolapplicationofanewtypeofauv
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