Wei He
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
Authors
Yongkun Sun
Zichen Yan
Charlie Yang Charlie.Yang@uwe.ac.uk
Professor in Robotics
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 |
Files
Disturbance Observer-Based Neural Network Control of Cooperative Multiple Manipulators with Input Saturation
(11.6 Mb)
PDF
Licence
http://www.rioxx.net/licenses/all-rights-reserved
Publisher Licence URL
http://www.rioxx.net/licenses/all-rights-reserved
Copyright Statement
(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
You might also like
Impedance learning for human-guided robots in contact with unknown environments
(2023)
Journal Article
A novel human-robot skill transfer method for contact-rich manipulation task
(2023)
Journal Article
A human-robot collaboration method for uncertain surface scanning
(2023)
Journal Article
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search