Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints
Yan Yang; Jiangtao Han; Zhijie Liu; Zhijia Zhao; Keum-Shik Hong
刊名IEEE/CAA Journal of Automatica Sinica
2023
卷号10期号:2页码:501-511
关键词Adaptive control cosserat theory prescribed motion constraints soft robotic arm
ISSN号2329-9266
DOI10.1109/JAS.2023.123213
英文摘要This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm. The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory. The unmodeled dynamics of the system are considered, and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network. The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory. The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/50862]  
专题自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式
GB/T 7714
Yan Yang,Jiangtao Han,Zhijie Liu,et al. Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(2):501-511.
APA Yan Yang,Jiangtao Han,Zhijie Liu,Zhijia Zhao,&Keum-Shik Hong.(2023).Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints.IEEE/CAA Journal of Automatica Sinica,10(2),501-511.
MLA Yan Yang,et al."Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints".IEEE/CAA Journal of Automatica Sinica 10.2(2023):501-511.
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