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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Bibliographic Details
Published inNonlinear dynamics Vol. 108; no. 4; pp. 3449 - 3466
Main Authors Ma, Ling, Lou, Xuyang, Wu, Wei, Huang, Xin
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.06.2022
Springer Nature B.V
Subjects
Automotive Engineering
Boundary control
Classical Mechanics
Control
Controllers
Dynamical Systems
Engineering
Feedback control
Gantry cranes
Mechanical Engineering
Neural networks
Original Paper
Vibration
Boundary control
Vibration control
Neural network
Gantry crane system
Input deadzone
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Summary: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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ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-022-07356-z