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Disturbance observer-based neural network control of cooperative multiple manipulators with input saturation

He, Wei; Sun, Yongkun; Yan, Zichen; Yang, Chenguang; Li, Zhijun; Kaynak, Okyay

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Authors

Wei He

Yongkun Sun

Zichen Yan

Zhijun Li

Okyay Kaynak



Abstract

In this paper, the complex problems of internal forces and position control are studied simultaneously and a disturbance observer-based radial basis function neural network (RBFNN) control scheme is proposed to: 1) estimate the unknown parameters accurately; 2) approximate the disturbance experienced by the system due to input saturation; and 3) simultaneously improve the robustness of the system. More specifically, the proposed scheme utilizes disturbance observers, neural network (NN) collaborative control with an adaptive law, and full state feedback. Utilizing Lyapunov stability principles, it is shown that semiglobally uniformly bounded stability is guaranteed for all controlled signals of the closed-loop system. The effectiveness of the proposed controller as predicted by the theoretical analysis is verified by comparative experimental studies.

Citation

He, W., Sun, Y., Yan, Z., Yang, C., Li, Z., & Kaynak, O. (2020). Disturbance observer-based neural network control of cooperative multiple manipulators with input saturation. IEEE Transactions on Neural Networks and Learning Systems, 31(5), 1735-1746. https://doi.org/10.1109/tnnls.2019.2923241

Journal Article Type Article
Acceptance Date Jun 2, 2019
Online Publication Date Aug 13, 2019
Publication Date May 1, 2020
Deposit Date Oct 29, 2019
Publicly Available Date Mar 29, 2024
Journal IEEE Transactions on Neural Networks and Learning Systems
Print ISSN 2162-237X
Electronic ISSN 2162-2388
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 31
Issue 5
Pages 1735-1746
DOI https://doi.org/10.1109/tnnls.2019.2923241
Keywords Computer Networks and Communications; Software; Artificial Intelligence; Computer Science Applications
Public URL https://uwe-repository.worktribe.com/output/4189860

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