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Adaptive Neural Network Control of Serial Variable Stiffness Actuators
Joint Authors
Sun, Tairen
Xiao, Xiaohui
Guo, Zhao
Zhang, Yubing
Pan, Yongping
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-08
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper focuses on modeling and control of a class of serial variable stiffness actuators (SVSAs) based on level mechanisms for robotic applications.
A multi-input multi-output complex nonlinear dynamic model is derived to fully describe SVSAs and the relative degree of the model is determined accordingly.
Due to nonlinearity, high coupling, and parametric uncertainty of SVSAs, a neural network-based adaptive control strategy based on feedback linearization is proposed to handle system uncertainties.
The feasibility of the proposed approach for position and stiffness tracking of SVSAs is verified by simulation results.
American Psychological Association (APA)
Guo, Zhao& Pan, Yongping& Sun, Tairen& Zhang, Yubing& Xiao, Xiaohui. 2017. Adaptive Neural Network Control of Serial Variable Stiffness Actuators. Complexity،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1143063
Modern Language Association (MLA)
Guo, Zhao…[et al.]. Adaptive Neural Network Control of Serial Variable Stiffness Actuators. Complexity No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1143063
American Medical Association (AMA)
Guo, Zhao& Pan, Yongping& Sun, Tairen& Zhang, Yubing& Xiao, Xiaohui. Adaptive Neural Network Control of Serial Variable Stiffness Actuators. Complexity. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1143063
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143063