Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression
In this paper, the precise control of the underwater manipulator has studied under the conditions of uncertain underwater dynamics and time-varying external interference. An improved adaptive model predictive control (MPC) method is proposed for a multiple-degrees-of-freedom (DOF) underwater manipul...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/9/1641 |
| _version_ | 1797579412016726016 |
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| author | Weidong Liu Jingming Xu Le Li Kang Zhang Hao Zhang |
| author_facet | Weidong Liu Jingming Xu Le Li Kang Zhang Hao Zhang |
| author_sort | Weidong Liu |
| collection | DOAJ |
| description | In this paper, the precise control of the underwater manipulator has studied under the conditions of uncertain underwater dynamics and time-varying external interference. An improved adaptive model predictive control (MPC) method is proposed for a multiple-degrees-of-freedom (DOF) underwater manipulator. In this method, the Gaussian process regression (GPR) algorithm has been embedded into the precise trajectory tracking control of the underwater manipulator. The GPR algorithm has been used to predict the water resistance, additional mass, buoyancy and external interference in real time, and the control law has been calculated by the terminal constraint MPC to realize the adaptive internal and external interference compensation. In addition, a more accurate dynamic model of the underwater 6-DOF manipulator is established by combining Lagrange equation with Morrison formula. Finally, the effectiveness of the adaptive MPC using GPR method is verified by a series of comparative simulations. |
| first_indexed | 2024-03-10T22:36:48Z |
| format | Article |
| id | doaj.art-fec78e1d91be48f2b6108e3451381e09 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T22:36:48Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-fec78e1d91be48f2b6108e3451381e092023-11-19T11:25:22ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-08-01119164110.3390/jmse11091641Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process RegressionWeidong Liu0Jingming Xu1Le Li2Kang Zhang3Hao Zhang4School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430223, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430223, ChinaIn this paper, the precise control of the underwater manipulator has studied under the conditions of uncertain underwater dynamics and time-varying external interference. An improved adaptive model predictive control (MPC) method is proposed for a multiple-degrees-of-freedom (DOF) underwater manipulator. In this method, the Gaussian process regression (GPR) algorithm has been embedded into the precise trajectory tracking control of the underwater manipulator. The GPR algorithm has been used to predict the water resistance, additional mass, buoyancy and external interference in real time, and the control law has been calculated by the terminal constraint MPC to realize the adaptive internal and external interference compensation. In addition, a more accurate dynamic model of the underwater 6-DOF manipulator is established by combining Lagrange equation with Morrison formula. Finally, the effectiveness of the adaptive MPC using GPR method is verified by a series of comparative simulations.https://www.mdpi.com/2077-1312/11/9/1641model predictive controlGaussian process regressionunderwater manipulator |
| spellingShingle | Weidong Liu Jingming Xu Le Li Kang Zhang Hao Zhang Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression Journal of Marine Science and Engineering model predictive control Gaussian process regression underwater manipulator |
| title | Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression |
| title_full | Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression |
| title_fullStr | Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression |
| title_full_unstemmed | Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression |
| title_short | Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression |
| title_sort | adaptive model predictive control for underwater manipulators using gaussian process regression |
| topic | model predictive control Gaussian process regression underwater manipulator |
| url | https://www.mdpi.com/2077-1312/11/9/1641 |
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