Adaptive Neural Network Control of ROVs under Ocean Current Disturbance
In view of the motion control problem of remotely operated vehicles(ROVs) under uncertain model parameters and ocean current disturbance, an adaptive back-stepping control system was designed based on the limited time command filtering and radial basis function(RBF) neural network. Firstly, a stocha...
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| Format: | Article |
| Language: | zho |
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Science Press (China)
2025-02-01
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| Series: | 水下无人系统学报 |
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| Online Access: | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0045 |
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| author | Xiangheng LI Zhaokun YAN Jiankun LOU Hongdong WANG |
| author_facet | Xiangheng LI Zhaokun YAN Jiankun LOU Hongdong WANG |
| author_sort | Xiangheng LI |
| collection | DOAJ |
| description | In view of the motion control problem of remotely operated vehicles(ROVs) under uncertain model parameters and ocean current disturbance, an adaptive back-stepping control system was designed based on the limited time command filtering and radial basis function(RBF) neural network. Firstly, a stochastic ocean current model based on the Markov process was constructed, and an ROV mathematical model under ocean current disturbance was established. Secondly, command filtering technology was introduced for the desired velocity to reduce the amount of calculation caused by the iterative derivative of the traditional back-stepping method. Thirdly, the RBF neural network was utilized to estimate the uncertainty terms and external unknown disturbances of the ROV model, and an adaptive neural network controller was designed. Finally, the Lyapunov stability theory was used to prove the stability of the closed-loop control system. The simulation results show that the controller designed in this paper can achieve precise control of ROV navigation and effectively suppress the impact of uncertainty term of the model and ocean current disturbance on ROV motion. |
| format | Article |
| id | doaj-art-6c7b33628359487d8778323fea4b2160 |
| institution | DOAJ |
| issn | 2096-3920 |
| language | zho |
| publishDate | 2025-02-01 |
| publisher | Science Press (China) |
| record_format | Article |
| series | 水下无人系统学报 |
| spelling | doaj-art-6c7b33628359487d8778323fea4b21602025-08-20T03:16:26ZzhoScience Press (China)水下无人系统学报2096-39202025-02-01331374510.11993/j.issn.2096-3920.2024-00452024-0045Adaptive Neural Network Control of ROVs under Ocean Current DisturbanceXiangheng LI0Zhaokun YAN1Jiankun LOU2Hongdong WANG3MOE Key Laboratory of Marine Intelligent Equipment and System, Shanghai Jiao Tong University, Shanghai 200240, ChinaMOE Key Laboratory of Marine Intelligent Equipment and System, Shanghai Jiao Tong University, Shanghai 200240, ChinaMOE Key Laboratory of Marine Intelligent Equipment and System, Shanghai Jiao Tong University, Shanghai 200240, ChinaMOE Key Laboratory of Marine Intelligent Equipment and System, Shanghai Jiao Tong University, Shanghai 200240, ChinaIn view of the motion control problem of remotely operated vehicles(ROVs) under uncertain model parameters and ocean current disturbance, an adaptive back-stepping control system was designed based on the limited time command filtering and radial basis function(RBF) neural network. Firstly, a stochastic ocean current model based on the Markov process was constructed, and an ROV mathematical model under ocean current disturbance was established. Secondly, command filtering technology was introduced for the desired velocity to reduce the amount of calculation caused by the iterative derivative of the traditional back-stepping method. Thirdly, the RBF neural network was utilized to estimate the uncertainty terms and external unknown disturbances of the ROV model, and an adaptive neural network controller was designed. Finally, the Lyapunov stability theory was used to prove the stability of the closed-loop control system. The simulation results show that the controller designed in this paper can achieve precise control of ROV navigation and effectively suppress the impact of uncertainty term of the model and ocean current disturbance on ROV motion.https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0045remotely operated vehicleocean current disturbancecommand filteringradial basis function neural network |
| spellingShingle | Xiangheng LI Zhaokun YAN Jiankun LOU Hongdong WANG Adaptive Neural Network Control of ROVs under Ocean Current Disturbance 水下无人系统学报 remotely operated vehicle ocean current disturbance command filtering radial basis function neural network |
| title | Adaptive Neural Network Control of ROVs under Ocean Current Disturbance |
| title_full | Adaptive Neural Network Control of ROVs under Ocean Current Disturbance |
| title_fullStr | Adaptive Neural Network Control of ROVs under Ocean Current Disturbance |
| title_full_unstemmed | Adaptive Neural Network Control of ROVs under Ocean Current Disturbance |
| title_short | Adaptive Neural Network Control of ROVs under Ocean Current Disturbance |
| title_sort | adaptive neural network control of rovs under ocean current disturbance |
| topic | remotely operated vehicle ocean current disturbance command filtering radial basis function neural network |
| url | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0045 |
| work_keys_str_mv | AT xianghengli adaptiveneuralnetworkcontrolofrovsunderoceancurrentdisturbance AT zhaokunyan adaptiveneuralnetworkcontrolofrovsunderoceancurrentdisturbance AT jiankunlou adaptiveneuralnetworkcontrolofrovsunderoceancurrentdisturbance AT hongdongwang adaptiveneuralnetworkcontrolofrovsunderoceancurrentdisturbance |