Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles
To promote the development of military and civilian applications for marine technology, more and more scientific research around the world has begun to develop unmanned surface vehicles (USVs) technology with advanced control capabilities. This paper establishes and identifies the model of vector pr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-12-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/9/1/22 |
| _version_ | 1798041347934912512 |
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| author | Xiaojie Sun Guofeng Wang Yunsheng Fan |
| author_facet | Xiaojie Sun Guofeng Wang Yunsheng Fan |
| author_sort | Xiaojie Sun |
| collection | DOAJ |
| description | To promote the development of military and civilian applications for marine technology, more and more scientific research around the world has begun to develop unmanned surface vehicles (USVs) technology with advanced control capabilities. This paper establishes and identifies the model of vector propulsion USV, which is widely used at present. After analyzing its actuator distribution, we consider that the more realistic vessel model should be an incomplete underactuated system. For this system, a virtual control point method is adopted and an adaptive sliding mode trajectory tracking controller with neural network minimum learning parameter (NNMLP) theory is designed. Finally, in the simulation experiment, the thruster speed and propulsion angle are used as the inputs of the controller, and the linear and circular trajectory tracking tests are carried out considering the delay effect of the actuator, system uncertainty, and external disturbance. The results show that the proposed tracking control framework is reasonable. |
| first_indexed | 2024-04-11T22:20:17Z |
| format | Article |
| id | doaj.art-a7cb00d39c7d4428a3d55823df5ab67a |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-04-11T22:20:17Z |
| publishDate | 2019-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-a7cb00d39c7d4428a3d55823df5ab67a2022-12-22T04:00:10ZengMDPI AGElectronics2079-92922019-12-01912210.3390/electronics9010022electronics9010022Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface VehiclesXiaojie Sun0Guofeng Wang1Yunsheng Fan2College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, ChinaCollege of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, ChinaCollege of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, ChinaTo promote the development of military and civilian applications for marine technology, more and more scientific research around the world has begun to develop unmanned surface vehicles (USVs) technology with advanced control capabilities. This paper establishes and identifies the model of vector propulsion USV, which is widely used at present. After analyzing its actuator distribution, we consider that the more realistic vessel model should be an incomplete underactuated system. For this system, a virtual control point method is adopted and an adaptive sliding mode trajectory tracking controller with neural network minimum learning parameter (NNMLP) theory is designed. Finally, in the simulation experiment, the thruster speed and propulsion angle are used as the inputs of the controller, and the linear and circular trajectory tracking tests are carried out considering the delay effect of the actuator, system uncertainty, and external disturbance. The results show that the proposed tracking control framework is reasonable.https://www.mdpi.com/2079-9292/9/1/22unmanned surface vehiclevector propulsionmodel identificationincomplete underactuated systemvirtual control pointminimum learning parameter |
| spellingShingle | Xiaojie Sun Guofeng Wang Yunsheng Fan Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles Electronics unmanned surface vehicle vector propulsion model identification incomplete underactuated system virtual control point minimum learning parameter |
| title | Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles |
| title_full | Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles |
| title_fullStr | Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles |
| title_full_unstemmed | Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles |
| title_short | Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles |
| title_sort | model identification and trajectory tracking control for vector propulsion unmanned surface vehicles |
| topic | unmanned surface vehicle vector propulsion model identification incomplete underactuated system virtual control point minimum learning parameter |
| url | https://www.mdpi.com/2079-9292/9/1/22 |
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