Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer
The motion of unmanned surface vehicles (USVs) is frequently disturbed by ocean wind, waves, and currents. A poorly designed controller will cause failures and safety problems during actual navigation. To obtain a satisfactory motion control performance for the USVs, a model predictive control (MPC)...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/10/1874 |
| _version_ | 1827720773180063744 |
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| author | Huixuan Fu Wenjing Yao Ricardo Cajo Shiquan Zhao |
| author_facet | Huixuan Fu Wenjing Yao Ricardo Cajo Shiquan Zhao |
| author_sort | Huixuan Fu |
| collection | DOAJ |
| description | The motion of unmanned surface vehicles (USVs) is frequently disturbed by ocean wind, waves, and currents. A poorly designed controller will cause failures and safety problems during actual navigation. To obtain a satisfactory motion control performance for the USVs, a model predictive control (MPC) method based on an improved Nonlinear Disturbance Observer (NDO) is proposed. First, the USV model is approximately linearized and MPC is designed for the multivariable system with constraints. To compensate for the influence of disturbances, an improved NDO is designed where the calculation time for MPC is reduced. Finally, comparison simulations are conducted between MPC with the original NDO and MPC with an improved NDO, and the results show that they have similar performances to the USVs. However, the proposed method has fewer parameters that need to be tuned and is much more time-saving compared to MPC with a traditional NDO. |
| first_indexed | 2024-03-10T21:09:10Z |
| format | Article |
| id | doaj.art-b9e3ff9e34924acb88fbee742ac34b61 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T21:09:10Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-b9e3ff9e34924acb88fbee742ac34b612023-11-19T16:57:55ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-09-011110187410.3390/jmse11101874Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance ObserverHuixuan Fu0Wenjing Yao1Ricardo Cajo2Shiquan Zhao3College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaFacultad de Ingeniería en Electricidad y Computación, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo Km 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil 090150, EcuadorCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaThe motion of unmanned surface vehicles (USVs) is frequently disturbed by ocean wind, waves, and currents. A poorly designed controller will cause failures and safety problems during actual navigation. To obtain a satisfactory motion control performance for the USVs, a model predictive control (MPC) method based on an improved Nonlinear Disturbance Observer (NDO) is proposed. First, the USV model is approximately linearized and MPC is designed for the multivariable system with constraints. To compensate for the influence of disturbances, an improved NDO is designed where the calculation time for MPC is reduced. Finally, comparison simulations are conducted between MPC with the original NDO and MPC with an improved NDO, and the results show that they have similar performances to the USVs. However, the proposed method has fewer parameters that need to be tuned and is much more time-saving compared to MPC with a traditional NDO.https://www.mdpi.com/2077-1312/11/10/1874unmanned surface vehicletrajectory trackingnonlinear disturbance observermodel predictive control |
| spellingShingle | Huixuan Fu Wenjing Yao Ricardo Cajo Shiquan Zhao Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer Journal of Marine Science and Engineering unmanned surface vehicle trajectory tracking nonlinear disturbance observer model predictive control |
| title | Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer |
| title_full | Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer |
| title_fullStr | Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer |
| title_full_unstemmed | Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer |
| title_short | Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer |
| title_sort | trajectory tracking predictive control for unmanned surface vehicles with improved nonlinear disturbance observer |
| topic | unmanned surface vehicle trajectory tracking nonlinear disturbance observer model predictive control |
| url | https://www.mdpi.com/2077-1312/11/10/1874 |
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