Adaptive neural network-based visual servoing control for manipulator with unknown output nonlinearities

doi:10.1016/j.ins.2018.03.057

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	Adaptive neural network-based visual servoing control for manipulator with unknown output nonlinearities
	Wang, Fujie 1; Liu, Zhi 1; Chen, C. L. P.2,3,4; Zhang, Yun 1
发表期刊	INFORMATION SCIENCES
ISSN	0020-0255
	2018-07-01
卷号	451 页码:16-33
通讯作者	Liu, Zhi(lz@gdut.edu.cn)
摘要	In this paper, the problem of neural network control for visual servoing robotic system is addressed, where the unmodeled dynamics and output nonlinearity are taken into account simultaneously. An adaptive neural network module is constructed to approach the unknown dynamics, upon which, the robot dynamics are not required to be linearly decomposable and structurally known. The major superiority of this module lies in its conciseness and the computational-reduction operation. Moreover, the output nonlinearity is considered, and its undesirable effect is subsequently tackled without a prior knowledge of the model parameters in output mechanism. It is proven by the Lyapunov method that the image-space tracking error is driven to an adjustable neighborhood of origin. Numerical simulations and experiments under various situations are used to validate the performance of the proposed adaptive neural network based scheme. (C) 2018 Elsevier Inc. All rights reserved.
关键词	Neural network-based control Adaptive control Unknown output nonlinearities Robotic manipulator Unknown dynamics
DOI	10.1016/j.ins.2018.03.057
关键词[WOS]	SLIDING-MODE CONTROL ; TRACKING CONTROL ; ROBOT MANIPULATORS ; UNCERTAIN KINEMATICS ; SYSTEMS ; CONSTRAINT ; DYNAMICS ; ACTUATOR ; DESIGN ; HYSTERESIS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61573108] ; National Natural Science Foundation of China[U1501251] ; Natural Science Foundation of Guangdong Province[2016A030313715] ; Natural Science Foundation of Guangdong Province through the Science Fund for Distinguished Young Scholars[S20120011437] ; Ministry of Education of New Century Excellent Talent[NCET-12-0637] ; National Natural Science Foundation of China[61573108] ; National Natural Science Foundation of China[U1501251] ; Natural Science Foundation of Guangdong Province[2016A030313715] ; Natural Science Foundation of Guangdong Province through the Science Fund for Distinguished Young Scholars[S20120011437] ; Ministry of Education of New Century Excellent Talent[NCET-12-0637]
项目资助者	National Natural Science Foundation of China ; Natural Science Foundation of Guangdong Province ; Natural Science Foundation of Guangdong Province through the Science Fund for Distinguished Young Scholars ; Ministry of Education of New Century Excellent Talent
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000432507900002
出版者	ELSEVIER SCIENCE INC
引用统计	被引频次：46[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/28194
专题	离退休人员
通讯作者	Liu, Zhi
作者单位	1.Guangdong Univ Technol, Fac Automat, Guangzhou 510006, Guangdong, Peoples R China 2.Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau 99999, Peoples R China 3.Dalian Maritime Univ, Dalian 116026, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Wang, Fujie,Liu, Zhi,Chen, C. L. P.,et al. Adaptive neural network-based visual servoing control for manipulator with unknown output nonlinearities[J]. INFORMATION SCIENCES,2018,451:16-33.
APA	Wang, Fujie,Liu, Zhi,Chen, C. L. P.,&Zhang, Yun.(2018).Adaptive neural network-based visual servoing control for manipulator with unknown output nonlinearities.INFORMATION SCIENCES,451,16-33.
MLA	Wang, Fujie,et al."Adaptive neural network-based visual servoing control for manipulator with unknown output nonlinearities".INFORMATION SCIENCES 451(2018):16-33.