CASIA OpenIR
Neural Networks Enhanced Adaptive Admittance Control of Optimized Robot-Environment Interaction
Yang, Chenguang1; Peng, Guangzhu1; Li, Yanan2; Cui, Rongxin3; Cheng, Long4,5; Li, Zhijun6
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
2019-07-01
Volume49Issue:7Pages:2568-2579
Corresponding AuthorYang, Chenguang(cyang@ieee.org)
AbstractIn this paper, an admittance adaptation method has been developed for robots to interact with unknown environments. The environment to be interacted with is modeled as a linear system. In the presence of the unknown dynamics of environments, an observer in robot joint space is employed to estimate the interaction torque, and admittance control is adopted to regulate the robot behavior at interaction points. An adaptive neural controller using the radial basis function is employed to guarantee trajectory tracking. A cost function that defines the interaction performance of torque regulation and trajectory tracking is minimized by admittance adaptation. To verify the proposed method, simulation studies on a robot manipulator are conducted.
KeywordAdmittance control neural networks (NNs) observer optimal adaptive control robot-environment interaction
DOI10.1109/TCYB.2018.2828654
WOS KeywordIMPEDANCE ; PARAMETERS ; VEHICLE
Indexed BySCI
Language英语
Funding ProjectNational Nature Science Foundation[61473120] ; National Nature Science Foundation[61633016] ; National Nature Science Foundation[61472325] ; Science and Technology Planning Project of Guangzhou[201607010006] ; Fundamental Research Funds for the Central Universities[2017ZD057] ; Research Fund for Young Top-Notch Talent of National Ten Thousand Talent Program ; Beijing Municipal Natural Science Foundation[4162066]
Funding OrganizationNational Nature Science Foundation ; Science and Technology Planning Project of Guangzhou ; Fundamental Research Funds for the Central Universities ; Research Fund for Young Top-Notch Talent of National Ten Thousand Talent Program ; Beijing Municipal Natural Science Foundation
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000466062500015
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24240
Collection中国科学院自动化研究所
Corresponding AuthorYang, Chenguang
Affiliation1.South China Univ Technol, Key Lab Autonomous Syst & Networked Control, Coll Automat Sci & Engn, Guangzhou 510640, Guangdong, Peoples R China
2.Univ Sussex, Dept Engn & Design, Brighton BN1 9RH, E Sussex, England
3.Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Shaanxi, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
6.Univ Sci & Technol China, Dept Automat, Hefei 230026, Anhui, Peoples R China
Recommended Citation
GB/T 7714
Yang, Chenguang,Peng, Guangzhu,Li, Yanan,et al. Neural Networks Enhanced Adaptive Admittance Control of Optimized Robot-Environment Interaction[J]. IEEE TRANSACTIONS ON CYBERNETICS,2019,49(7):2568-2579.
APA Yang, Chenguang,Peng, Guangzhu,Li, Yanan,Cui, Rongxin,Cheng, Long,&Li, Zhijun.(2019).Neural Networks Enhanced Adaptive Admittance Control of Optimized Robot-Environment Interaction.IEEE TRANSACTIONS ON CYBERNETICS,49(7),2568-2579.
MLA Yang, Chenguang,et al."Neural Networks Enhanced Adaptive Admittance Control of Optimized Robot-Environment Interaction".IEEE TRANSACTIONS ON CYBERNETICS 49.7(2019):2568-2579.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang, Chenguang]'s Articles
[Peng, Guangzhu]'s Articles
[Li, Yanan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang, Chenguang]'s Articles
[Peng, Guangzhu]'s Articles
[Li, Yanan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang, Chenguang]'s Articles
[Peng, Guangzhu]'s Articles
[Li, Yanan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.