Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction
This paper studies the trajectory tracking problem of an underactuated autonomous underwater vehicle (AUV) under the uncertainty of model parameters and input delay. Different from previous algorithms, a novel control algorithm is proposed which is a combination of RBF neural network algorithm and s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8930028/ |
| _version_ | 1818412611643899904 |
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| author | Jiajia Zhou Xinyi Zhao Tao Chen Zheping Yan Zewen Yang |
| author_facet | Jiajia Zhou Xinyi Zhao Tao Chen Zheping Yan Zewen Yang |
| author_sort | Jiajia Zhou |
| collection | DOAJ |
| description | This paper studies the trajectory tracking problem of an underactuated autonomous underwater vehicle (AUV) under the uncertainty of model parameters and input delay. Different from previous algorithms, a novel control algorithm is proposed which is a combination of RBF neural network algorithm and state prediction using backstepping sliding mode control method. The RBF neural network algorithm is used to estimate the composite interferences of model parameter uncertainties and external disturbances. Meanwhile, an appropriate virtual control law is designed for the horizontal trajectory tracking of the underactuated AUV by backstepping technique. Further, the longitudinal and heading control laws are proposed using the nonsingular fast terminal sliding mode method. Then, it is proved that the AUV velocity tracking error can converge to zero in a finite time by the Lyapunov theory. Finally, the effectiveness and robustness of the approach is illustrated by the simulation results. |
| first_indexed | 2024-12-14T10:50:04Z |
| format | Article |
| id | doaj.art-1d10e3210b094411a4b25eef053e3c82 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T10:50:04Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1d10e3210b094411a4b25eef053e3c822022-12-21T23:05:15ZengIEEEIEEE Access2169-35362019-01-01718198318199310.1109/ACCESS.2019.29583608930028Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State PredictionJiajia Zhou0https://orcid.org/0000-0001-9974-3231Xinyi Zhao1https://orcid.org/0000-0002-9526-0352Tao Chen2https://orcid.org/0000-0002-8702-339XZheping Yan3https://orcid.org/0000-0002-5598-0275Zewen Yang4College of Automation, Harbin Engineering University, Harbin, ChinaCollege of Automation, Harbin Engineering University, Harbin, ChinaCollege of Automation, Harbin Engineering University, Harbin, ChinaCollege of Automation, Harbin Engineering University, Harbin, ChinaCollege of Automation, Harbin Engineering University, Harbin, ChinaThis paper studies the trajectory tracking problem of an underactuated autonomous underwater vehicle (AUV) under the uncertainty of model parameters and input delay. Different from previous algorithms, a novel control algorithm is proposed which is a combination of RBF neural network algorithm and state prediction using backstepping sliding mode control method. The RBF neural network algorithm is used to estimate the composite interferences of model parameter uncertainties and external disturbances. Meanwhile, an appropriate virtual control law is designed for the horizontal trajectory tracking of the underactuated AUV by backstepping technique. Further, the longitudinal and heading control laws are proposed using the nonsingular fast terminal sliding mode method. Then, it is proved that the AUV velocity tracking error can converge to zero in a finite time by the Lyapunov theory. Finally, the effectiveness and robustness of the approach is illustrated by the simulation results.https://ieeexplore.ieee.org/document/8930028/Underactuated AUVtrajectory trackingsliding mode methodstate predictionbackstepping technique |
| spellingShingle | Jiajia Zhou Xinyi Zhao Tao Chen Zheping Yan Zewen Yang Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction IEEE Access Underactuated AUV trajectory tracking sliding mode method state prediction backstepping technique |
| title | Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction |
| title_full | Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction |
| title_fullStr | Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction |
| title_full_unstemmed | Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction |
| title_short | Trajectory Tracking Control of an Underactuated AUV Based on Backstepping Sliding Mode With State Prediction |
| title_sort | trajectory tracking control of an underactuated auv based on backstepping sliding mode with state prediction |
| topic | Underactuated AUV trajectory tracking sliding mode method state prediction backstepping technique |
| url | https://ieeexplore.ieee.org/document/8930028/ |
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