Robust fault accommodation approach for double-pendulum tower cranes via adaptive neural network-triggered control-Reference-Cited by-同舟云学术

Robust fault accommodation approach for double-pendulum tower cranes via adaptive neural network-triggered control

Published:2023-09-29 Issue:21 Volume:111 Page:19993-20013
ISSN:0924-090X
Container-title:Nonlinear Dynamics
language:en
Short-container-title:Nonlinear Dyn

Author:

Zhang Menghua^ORCID,Jing Xingjian,Huang Weijie,Lu Quanli,Chen Jiyang,Chen Zhenxue

Funder

the Startup Fund of City University of Hong Kong

Hong Kong Research Institute of Textiles and Apparel

the Key R&D Project of Shandong Province

the National Natural Science Foundation for Young Scientists of China

the Youth Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Mechanical Engineering,Ocean Engineering,Aerospace Engineering,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11071-023-08891-z.pdf

Reference36 articles.

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2. Peng, J., Huang, J., Singhose, W.: Payload twisting dynamics and oscillation suppression of tower cranes during slewing motions. Nonlinear Dyn. 98, 1041–1048 (2019). https://doi.org/10.1007/s11071-019-05247-4

3. Wu, Z., Xia, X.: Optimal motion planning for overhead cranes. IET Control Theory Appl. 8(17), 1833–1842 (2014). https://doi.org/10.1049/iet-cta.2014.0069

4. Zhang, X., Fang, Y., Sun, N.: Minimum-time trajectory planning for underactuated overhead crane systems with state and control constraints. IEEE Trans. Ind. Electron. 61(12), 6915–6925 (2014). https://doi.org/10.1109/TIE.2014.2320231

5. Pan, H., Jing, X., Sun, W., Gao, H.: A bioinspired dynamics-based adaptive tracking control for nonlinear suspension systems. IEEE Trans. Control Syst. Technol. 26(3), 903–914 (2018). https://doi.org/10.1109/TCST.2017.2699158

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