A Data-Driven Cyclic-Motion Generation Scheme for Kinematic Control of Redundant Manipulators

doi:10.1109/TCST.2019.2963017

	A Data-Driven Cyclic-Motion Generation Scheme for Kinematic Control of Redundant Manipulators
	Xie, Zhengtai 1,2; Jin, Long 1,2; Luo, Xin 4,5,6; Li, Shuai 1,2; Xiao, Xiuchun 3
刊名	IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
	2021
卷号	29 期号:1 页码:53-63
关键词	Manipulator dynamics Kinematics Task analysis Jacobian matrices Neural networks Redundancy Cyclic-motion generation (CMG) data driven dynamic neural network (DNN) learning and control redundant manipulator
ISSN号	1063-6536
DOI	10.1109/TCST.2019.2963017
通讯作者	Jin, Long(jinlongsysu@foxmail.com)
英文摘要	Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation (CMG) task, to some extent. Inspired by this problem, this article proposes a data-driven CMG scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously to complete the kinematic control of manipulators with model unknown. It is worth mentioning that the proposed method is capable of accurately estimating the Jacobian matrix in order to obtain the structure information of the manipulator and theoretically eliminates the tracking errors. Theoretical analyses prove the convergence of the learning and control parts under the necessary noise conditions. Computer simulation results and comparisons of different controllers illustrate the reliability and superior performance of the proposed method with strong learning ability and control ability. This article is greatly significant for redundancy resolution of redundant manipulators with unknown models or unknown loads in practice.
资助项目	National Natural Science Foundation of China[61703189] ; Natural Science Foundation of Gansu Province, China[18JR3RA264] ; Natural Science Foundation of Chongqing (China)[cstc2019jcyjjqX0013] ; Pioneer Hundred Talents Program of Chinese Academy of Sciences ; Sichuan Science and Technology Program[19YYJC1656] ; National Key Research and Development Program of China[2017YFE0118900] ; Innovation and Strength Project in Guangdong Province (Natural Science)[230419065] ; Industry-UniversityResearch Cooperation Education Project of Ministry of Education[201801328005] ; Fundamental Research Funds for the Central Universities[lzujbky-2019-89]
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000600848100005
内容类型	期刊论文
源URL	[http://119.78.100.138/handle/2HOD01W0/12664]
专题	中国科学院重庆绿色智能技术研究院
通讯作者	Jin, Long
作者单位	1.Acad Plateau Sci & Sustainabil, Xining 810016, Peoples R China 2.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China 3.Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524000, Peoples R China 4.Cloudwalk, Dept Big Data Analyses Tech, Chongqing 401331, Peoples R China 5.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China 6.Chinese Acad Sci, Chongqing Engn Res Ctr Big Data Applicat Smart Ci, Chongqing 400714, Peoples R China
推荐引用方式 GB/T 7714	Xie, Zhengtai,Jin, Long,Luo, Xin,et al. A Data-Driven Cyclic-Motion Generation Scheme for Kinematic Control of Redundant Manipulators[J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY,2021,29(1):53-63.
APA	Xie, Zhengtai,Jin, Long,Luo, Xin,Li, Shuai,&Xiao, Xiuchun.(2021).A Data-Driven Cyclic-Motion Generation Scheme for Kinematic Control of Redundant Manipulators.IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY,29(1),53-63.
MLA	Xie, Zhengtai,et al."A Data-Driven Cyclic-Motion Generation Scheme for Kinematic Control of Redundant Manipulators".IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 29.1(2021):53-63.