CASIA OpenIR
Robust global consensus tracking of linear multi-agent systems with input saturation via scheduled low-and-high gain feedback
Chu, Hongjun1,2; Chen, Jianliang3; Wei, Qinglai4; Zhang, Weidong2
Source PublicationIET CONTROL THEORY AND APPLICATIONS
ISSN1751-8644
2019
Volume13Issue:1Pages:69-77
Corresponding AuthorZhang, Weidong(wdzhang@sjtu.edu.cn)
AbstractThis study deals with the protocol design for achieving robust global consensus tracking of multi-agent systems. Agent dynamics are described as general linear systems with actuator saturation and input additive uncertainties and disturbances. Via developing a scheduled low-and-high gain design technique, the state feedback protocol is proposed, under which global consensus tracking and disturbance rejection for such systems can be achieved under the mild assumptions on agent dynamics and network topology. This result is further extended to the case of the reduced-order observer-based protocol design, with the help of the special coordinate basis approach. Finally, the advantages of the proposed protocols are illustrated by a numerical simulation.
Keywordreduced order systems observers multi-agent systems linear systems multi-robot systems actuators robust control state feedback feedback control system synthesis topology robust global consensus tracking input saturation agent dynamics general linear systems actuator saturation input additive uncertainties state feedback protocol disturbance rejection reduced-order observer-based protocol design linear multi-agent systems scheduled low-and-high gain feedback network topology
DOI10.1049/iet-cta.2018.5347
WOS KeywordLEADER-FOLLOWING CONSENSUS ; CONTAINMENT CONTROL ; ACTUATOR SATURATION ; SYNCHRONIZATION ; OBSERVER ; ALGORITHMS ; NETWORKS ; DYNAMICS ; SUBJECT ; DESIGN
Indexed BySCI
Language英语
Funding ProjectNational Science Foundation of China[61473183] ; National Science Foundation of China[U1509211] ; National Science Foundation of China[61627810] ; National Science Foundation of China[61722312] ; National Science Foundation of China[61471275] ; National Science Foundation of China[61603253] ; National Key R&D Program of China[SQ2017YFGH001005] ; Natural Science Foundation of Hubei Province of China[2017CFB719] ; NUPTSF[NY218145]
Funding OrganizationNational Science Foundation of China ; National Key R&D Program of China ; Natural Science Foundation of Hubei Province of China ; NUPTSF
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000455640300007
PublisherINST ENGINEERING TECHNOLOGY-IET
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25332
Collection中国科学院自动化研究所
Corresponding AuthorZhang, Weidong
Affiliation1.Nanjing Univ Posts & Telecommun, Inst Adv Technol, Nanjing 210023, Jiangsu, Peoples R China
2.Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
3.Wuhan Univ Sci & Technol, Minist Educ, Engn Res Ctr Met Automat & Detecting Technol, Wuhan 430081, Hubei, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Chu, Hongjun,Chen, Jianliang,Wei, Qinglai,et al. Robust global consensus tracking of linear multi-agent systems with input saturation via scheduled low-and-high gain feedback[J]. IET CONTROL THEORY AND APPLICATIONS,2019,13(1):69-77.
APA Chu, Hongjun,Chen, Jianliang,Wei, Qinglai,&Zhang, Weidong.(2019).Robust global consensus tracking of linear multi-agent systems with input saturation via scheduled low-and-high gain feedback.IET CONTROL THEORY AND APPLICATIONS,13(1),69-77.
MLA Chu, Hongjun,et al."Robust global consensus tracking of linear multi-agent systems with input saturation via scheduled low-and-high gain feedback".IET CONTROL THEORY AND APPLICATIONS 13.1(2019):69-77.
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
[Chu, Hongjun]'s Articles
[Chen, Jianliang]'s Articles
[Wei, Qinglai]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chu, Hongjun]'s Articles
[Chen, Jianliang]'s Articles
[Wei, Qinglai]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chu, Hongjun]'s Articles
[Chen, Jianliang]'s Articles
[Wei, Qinglai]'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.