Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter
This paper proposes a zero-speed vessel fin stabilizer adaptive neural network control strategy based on a command filter for the problem of large-angle rolling motion caused by adverse sea conditions when a vessel is at low speed down to zero. In order to avoid the adverse effects of the high-frequ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/2/754 |
| _version_ | 1797496115857195008 |
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| author | Ziteng Sun Chao Chen Guibing Zhu |
| author_facet | Ziteng Sun Chao Chen Guibing Zhu |
| author_sort | Ziteng Sun |
| collection | DOAJ |
| description | This paper proposes a zero-speed vessel fin stabilizer adaptive neural network control strategy based on a command filter for the problem of large-angle rolling motion caused by adverse sea conditions when a vessel is at low speed down to zero. In order to avoid the adverse effects of the high-frequency part of the marine environment on the vessel rolling control system, a command filter is introduced in the design of the controller and a command filter backstepping control method is designed. An auxiliary dynamic system (ADS) is constructed to correct the feedback error caused by input saturation. Considering that the system has unknown internal parameters and unmodeled dynamics, and is affected by unknown disturbances from the outside, the neural network technology and nonlinear disturbance observer are fused in the proposed design, which not only combines the advantages of the two but also overcomes the limitations of the single technique itself. Through Lyapunov theoretical analysis, the stability of the control system is proved. Finally, the simulation results also verify the effectiveness of the control method. |
| first_indexed | 2024-03-10T01:59:03Z |
| format | Article |
| id | doaj.art-a005331dbd82428f911071f38539a1bb |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T01:59:03Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-a005331dbd82428f911071f38539a1bb2023-11-23T12:52:13ZengMDPI AGApplied Sciences2076-34172022-01-0112275410.3390/app12020754Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command FilterZiteng Sun0Chao Chen1Guibing Zhu2Maritime College, Zhejiang Ocean University, Zhoushan 316000, ChinaMaritime College, Zhejiang Ocean University, Zhoushan 316000, ChinaMaritime College, Zhejiang Ocean University, Zhoushan 316000, ChinaThis paper proposes a zero-speed vessel fin stabilizer adaptive neural network control strategy based on a command filter for the problem of large-angle rolling motion caused by adverse sea conditions when a vessel is at low speed down to zero. In order to avoid the adverse effects of the high-frequency part of the marine environment on the vessel rolling control system, a command filter is introduced in the design of the controller and a command filter backstepping control method is designed. An auxiliary dynamic system (ADS) is constructed to correct the feedback error caused by input saturation. Considering that the system has unknown internal parameters and unmodeled dynamics, and is affected by unknown disturbances from the outside, the neural network technology and nonlinear disturbance observer are fused in the proposed design, which not only combines the advantages of the two but also overcomes the limitations of the single technique itself. Through Lyapunov theoretical analysis, the stability of the control system is proved. Finally, the simulation results also verify the effectiveness of the control method.https://www.mdpi.com/2076-3417/12/2/754command filteringinput saturationadaptive controlnonlinear disturbance observerRBF neural network |
| spellingShingle | Ziteng Sun Chao Chen Guibing Zhu Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter Applied Sciences command filtering input saturation adaptive control nonlinear disturbance observer RBF neural network |
| title | Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter |
| title_full | Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter |
| title_fullStr | Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter |
| title_full_unstemmed | Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter |
| title_short | Adaptive Neural Network Control of Zero-Speed Vessel Fin Stabilizer Based on Command Filter |
| title_sort | adaptive neural network control of zero speed vessel fin stabilizer based on command filter |
| topic | command filtering input saturation adaptive control nonlinear disturbance observer RBF neural network |
| url | https://www.mdpi.com/2076-3417/12/2/754 |
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