Neural network-based boundary control of a gantry crane system subject to input deadzone and external disturbance
This paper is concerned with designing a neural network-based boundary controller to stabilize the gantry crane system subject to input deadzone and external disturbance. More explicitly, a boundary controller acting on the trolley is developed together with adopting a neural network to compensate f...
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| Published in | Nonlinear dynamics Vol. 108; no. 4; pp. 3449 - 3466 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.06.2022
Springer Nature B.V |
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| Abstract | This paper is concerned with designing a neural network-based boundary controller to stabilize the gantry crane system subject to input deadzone and external disturbance. More explicitly, a boundary controller acting on the trolley is developed together with adopting a neural network to compensate for the unknown nonlinearity of the input deadzone. Subsequently, based on the Lyapunov stability theory, we show that the solution to the closed-loop system is both uniformly bounded and uniformly ultimately bounded. Finally, both numerical simulations and physical experiment results are provided to demonstrate the effectiveness of the proposed method. |
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| AbstractList | This paper is concerned with designing a neural network-based boundary controller to stabilize the gantry crane system subject to input deadzone and external disturbance. More explicitly, a boundary controller acting on the trolley is developed together with adopting a neural network to compensate for the unknown nonlinearity of the input deadzone. Subsequently, based on the Lyapunov stability theory, we show that the solution to the closed-loop system is both uniformly bounded and uniformly ultimately bounded. Finally, both numerical simulations and physical experiment results are provided to demonstrate the effectiveness of the proposed method. |
| Author | Wu, Wei Huang, Xin Ma, Ling Lou, Xuyang |
| Author_xml | – sequence: 1 givenname: Ling surname: Ma fullname: Ma, Ling organization: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University – sequence: 2 givenname: Xuyang orcidid: 0000-0002-7499-1308 surname: Lou fullname: Lou, Xuyang email: Louxy@jiangnan.edu.cn organization: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University – sequence: 3 givenname: Wei surname: Wu fullname: Wu, Wei organization: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University – sequence: 4 givenname: Xin surname: Huang fullname: Huang, Xin organization: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University |
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| Cites_doi | 10.1177/1077546319876147 10.1109/TNNLS.2015.2471262 10.1016/j.automatica.2015.12.026 10.1109/TNNLS.2018.2869375 10.1109/TIE.2015.2400427 10.1016/j.ymssp.2018.03.058 10.1016/j.neucom.2017.09.050 10.1007/s12206-009-1020-1 10.1007/s11071-017-3595-x 10.1007/s11071-015-2275-y 10.1109/TNNLS.2019.2910580 10.1007/s11071-021-06443-x 10.1016/j.automatica.2003.10.021 10.1016/j.jfranklin.2018.06.014 10.1109/TIE.2013.2288200 10.1007/s11071-020-05471-3 10.1007/978-3-662-04641-8 10.1007/s11633-018-1122-2 10.1109/TCST.2013.2278279 10.1109/TSMC.2019.2912900 10.1109/TSMC.2015.2466194 10.1016/j.jsv.2020.115274 10.1023/A:1008333417693 10.1109/TIE.2013.2251731 10.1002/rnc.3381 10.1016/S0005-1098(99)00182-X 10.1137/1.9780898718607 |
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| Keywords | Boundary control Vibration control Neural network Gantry crane system Input deadzone |
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| StartPage | 3449 |
| SubjectTerms | Automotive Engineering Boundary control Classical Mechanics Control Controllers Dynamical Systems Engineering Feedback control Gantry cranes Mechanical Engineering Neural networks Original Paper Vibration |
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| Title | Neural network-based boundary control of a gantry crane system subject to input deadzone and external disturbance |
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