Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance
In this study, a new neural observer-based dynamic surface control scheme is proposed for the path following of underactuated unmanned surface vessels in the presence of input saturation and time-varying external disturbance. The dynamic surface control technique is augmented by a robust adaptive ra...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2019-10-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/1729881419878071 |
| _version_ | 1828472059662958592 |
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| author | Lei Wan Jiangfeng Zeng Yueming Li Hongde Qin Lei Zhang Jian Wang |
| author_facet | Lei Wan Jiangfeng Zeng Yueming Li Hongde Qin Lei Zhang Jian Wang |
| author_sort | Lei Wan |
| collection | DOAJ |
| description | In this study, a new neural observer-based dynamic surface control scheme is proposed for the path following of underactuated unmanned surface vessels in the presence of input saturation and time-varying external disturbance. The dynamic surface control technique is augmented by a robust adaptive radial basis function neural network and a nonlinear neural disturbance observer. Radial basis function neural network is employed to deal with system uncertainties, and the nonlinear neural disturbance observer is developed to compensate for the unknown compound disturbance that contains the input saturation approximation error and the external disturbance. Moreover, the stringent known boundary requirement of the unknown disturbance constraint is eliminated with the proposed nonlinear neural disturbance observer. Meanwhile, to deal with the non-smooth saturation nonlinearity, a new parametric hyperbolic tangent function approximation model with arbitrary prescribed precision is constructed, which results in the transient performance improvement for the path following control system. Stability analysis shows that all the signals in the closed-loop system are guaranteed to be ultimately bounded. Comparative simulation results further demonstrate the effectiveness of the proposed control scheme. |
| first_indexed | 2024-12-11T05:22:41Z |
| format | Article |
| id | doaj.art-bddcdb60cb2844148b851bdfcea8b672 |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-11T05:22:41Z |
| publishDate | 2019-10-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-bddcdb60cb2844148b851bdfcea8b6722022-12-22T01:19:39ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142019-10-011610.1177/1729881419878071Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbanceLei Wan0Jiangfeng Zeng1Yueming Li2Hongde Qin3Lei Zhang4Jian Wang5 Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China CSSC System Engineering Research Institute, Beijing, China Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China Marine Design and Research Institute of China, Shanghai, ChinaIn this study, a new neural observer-based dynamic surface control scheme is proposed for the path following of underactuated unmanned surface vessels in the presence of input saturation and time-varying external disturbance. The dynamic surface control technique is augmented by a robust adaptive radial basis function neural network and a nonlinear neural disturbance observer. Radial basis function neural network is employed to deal with system uncertainties, and the nonlinear neural disturbance observer is developed to compensate for the unknown compound disturbance that contains the input saturation approximation error and the external disturbance. Moreover, the stringent known boundary requirement of the unknown disturbance constraint is eliminated with the proposed nonlinear neural disturbance observer. Meanwhile, to deal with the non-smooth saturation nonlinearity, a new parametric hyperbolic tangent function approximation model with arbitrary prescribed precision is constructed, which results in the transient performance improvement for the path following control system. Stability analysis shows that all the signals in the closed-loop system are guaranteed to be ultimately bounded. Comparative simulation results further demonstrate the effectiveness of the proposed control scheme.https://doi.org/10.1177/1729881419878071 |
| spellingShingle | Lei Wan Jiangfeng Zeng Yueming Li Hongde Qin Lei Zhang Jian Wang Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance International Journal of Advanced Robotic Systems |
| title | Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance |
| title_full | Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance |
| title_fullStr | Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance |
| title_full_unstemmed | Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance |
| title_short | Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance |
| title_sort | neural observer based path following control for underactuated unmanned surface vessels with input saturation and time varying disturbance |
| url | https://doi.org/10.1177/1729881419878071 |
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