Adaptive Neural Self-Triggered Bipartite Fault-Tolerant Control for Nonlinear MASs With Dead-Zone Constraints

An adaptive neural bipartite tracking control approach is proposed for nonlinear multi-agent systems in this article. In contrast to previous results, it is worth noting that this paper considers a cooperative-competitive relationship in multi-agent systems, which stands for a more common situation....

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on automation science and engineering Vol. 20; no. 3; pp. 1663 - 1674
Main Authors Cheng, Fabin, Liang, Hongjing, Wang, Huanqing, Zong, Guangdeng, Xu, Ning
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text

Cover

Loading…
Abstract An adaptive neural bipartite tracking control approach is proposed for nonlinear multi-agent systems in this article. In contrast to previous results, it is worth noting that this paper considers a cooperative-competitive relationship in multi-agent systems, which stands for a more common situation. In this paper, a distributed self-triggered communication strategy is designed to improve the transmission efficiency of the whole system. In addition, the designed controller can compensate the actuator failure and dead-zone nonlinearity, and increases the system fault-tolerance. The proposed method ensures the boundedness of all signals of the closed-loop system and the bipartite tracking performance. The effectiveness of the proposed method is verified by two simulation examples. Note to Practitioners -Since complex modern engineering systems are difficult to be controlled by a single component, the cooperative control mode of multi-agent systems has become the mainstream trend. For multi-agent systems with cooperative-competitive relationships, the unique bipartite consensus will allow each agent to better complete the control objectives according to their respective advantages. In addition, for engineering systems such as automated manufacturing systems and transportation systems, fault problems are becoming more commonplace. These faults may make the system difficult to operate normally, and then affect the project progress. Therefore, how to guarantee the normal work of the control system when subject to faults has become a key topic. On the other hand, the channel bandwidth of the actual communication system is limited, and frequent updating of control signals will produce huge communication pressure in the traditional control scheme. Hence, it is challenging to design a control strategy that can achieve system stability and reduce communication resources simultaneously. This paper discusses the bipartite fault-tolerant control problem for nonlinear multi-agent systems. Meanwhile, a distributed adaptive self-triggered mechanism is designed to save communication resources.
AbstractList An adaptive neural bipartite tracking control approach is proposed for nonlinear multi-agent systems in this article. In contrast to previous results, it is worth noting that this paper considers a cooperative-competitive relationship in multi-agent systems, which stands for a more common situation. In this paper, a distributed self-triggered communication strategy is designed to improve the transmission efficiency of the whole system. In addition, the designed controller can compensate the actuator failure and dead-zone nonlinearity, and increases the system fault-tolerance. The proposed method ensures the boundedness of all signals of the closed-loop system and the bipartite tracking performance. The effectiveness of the proposed method is verified by two simulation examples. Note to Practitioners —Since complex modern engineering systems are difficult to be controlled by a single component, the cooperative control mode of multi-agent systems has become the mainstream trend. For multi-agent systems with cooperative-competitive relationships, the unique bipartite consensus will allow each agent to better complete the control objectives according to their respective advantages. In addition, for engineering systems such as automated manufacturing systems and transportation systems, fault problems are becoming more commonplace. These faults may make the system difficult to operate normally, and then affect the project progress. Therefore, how to guarantee the normal work of the control system when subject to faults has become a key topic. On the other hand, the channel bandwidth of the actual communication system is limited, and frequent updating of control signals will produce huge communication pressure in the traditional control scheme. Hence, it is challenging to design a control strategy that can achieve system stability and reduce communication resources simultaneously. This paper discusses the bipartite fault-tolerant control problem for nonlinear multi-agent systems. Meanwhile, a distributed adaptive self-triggered mechanism is designed to save communication resources.
Author Wang, Huanqing
Liang, Hongjing
Xu, Ning
Cheng, Fabin
Zong, Guangdeng
Author_xml – sequence: 1
  givenname: Fabin
  orcidid: 0000-0001-7120-4164
  surname: Cheng
  fullname: Cheng, Fabin
  email: chengfabin184@gmail.com
  organization: College of Control Science and Engineering, Bohai University, Jinzhou, China
– sequence: 2
  givenname: Hongjing
  orcidid: 0000-0003-1480-1872
  surname: Liang
  fullname: Liang, Hongjing
  email: lianghongjing99@163.com
  organization: College of Control Science and Engineering, Bohai University, Jinzhou, China
– sequence: 3
  givenname: Huanqing
  orcidid: 0000-0001-5712-9356
  surname: Wang
  fullname: Wang, Huanqing
  email: ndwhq@163.com
  organization: College of Mathematical Science, Bohai University, Jinzhou, China
– sequence: 4
  givenname: Guangdeng
  orcidid: 0000-0001-6498-5580
  surname: Zong
  fullname: Zong, Guangdeng
  email: lovelyletian@gmail.com
  organization: School of Control Science and Engineering, Tiangong University, Tianjin, China
– sequence: 5
  givenname: Ning
  orcidid: 0000-0002-0717-1713
  surname: Xu
  fullname: Xu, Ning
  email: hpxuning@163.com
  organization: Institute of Information and Control, Hangzhou Dianzi University, Hangzhou, China
BookMark eNp9kMlOwzAQhi0EEmV5AMTFEucUr419LKUsEsuhQUhcIicZg6sQF9tB4u1JVMSBA6eZw__N8h2g3c53gNAJJVNKiT4v5qvllBHGppwqMdQdNKFSqozniu-OvZCZ1FLuo4MY14QwoTSZoPd5YzbJfQJ-gD6YFq-gtVkR3OsrBGjwhduYkFwCfGX6NmWFbyGYLuGF71LwLbY-4Affta4DE_D9fBXxs0tv-BJMk70MR47JmIJxXYpHaM-aNsLxTz1ET1fLYnGT3T1e3y7md1nNNE-Z1pBLqiqhK22ltnRGuK0bwSjTkpMq5xVRYBkjfCYsI5IYzo2ZESEEq3nFD9HZdu4m-I8eYirXvg_dsLJkilPJ2CBpSOXbVB18jAFsWbtkkhs_M64tKSlHt-Xothzdlj9uB5L-ITfBvZvw9S9zumUcAPzmtaJE5YR_AxO4hb0
CODEN ITASC7
CitedBy_id crossref_primary_10_1109_TASE_2023_3340849
crossref_primary_10_1007_s40815_023_01560_8
crossref_primary_10_1016_j_amc_2024_128585
crossref_primary_10_1007_s10723_023_09651_4
crossref_primary_10_1080_00207721_2023_2169845
crossref_primary_10_1109_TASE_2023_3317902
crossref_primary_10_1007_s40815_024_01834_9
crossref_primary_10_1109_TASE_2023_3298343
crossref_primary_10_1109_TASE_2024_3390007
crossref_primary_10_1016_j_neucom_2024_128668
crossref_primary_10_1016_j_oceaneng_2024_119473
crossref_primary_10_1109_TFUZZ_2024_3423709
crossref_primary_10_1109_TITS_2023_3300911
crossref_primary_10_1016_j_jfranklin_2024_107241
crossref_primary_10_1109_TASE_2024_3411074
crossref_primary_10_1109_TAI_2023_3318895
crossref_primary_10_1109_TASE_2024_3432131
crossref_primary_10_1016_j_ins_2024_121619
crossref_primary_10_1093_imamci_dnae010
crossref_primary_10_1002_acs_3730
crossref_primary_10_1109_TASE_2023_3296259
crossref_primary_10_1109_TASE_2024_3436927
crossref_primary_10_1109_TASE_2024_3427771
crossref_primary_10_1109_TASE_2023_3349150
crossref_primary_10_1109_TASE_2024_3391312
crossref_primary_10_1109_TNSE_2023_3273205
crossref_primary_10_1002_ett_4905
crossref_primary_10_1088_1361_6501_ad9e27
crossref_primary_10_1016_j_sasc_2025_200197
crossref_primary_10_1002_rnc_7634
crossref_primary_10_1109_TASE_2023_3324397
crossref_primary_10_1002_rnc_6820
crossref_primary_10_1109_TIM_2023_3336446
crossref_primary_10_1177_09544100241240161
crossref_primary_10_1002_rnc_7112
crossref_primary_10_1109_TASE_2023_3324953
crossref_primary_10_3390_math11081845
crossref_primary_10_1109_TFUZZ_2023_3323650
crossref_primary_10_1093_imamci_dnae002
crossref_primary_10_1080_00051144_2023_2217601
crossref_primary_10_1109_TASE_2024_3439747
crossref_primary_10_1109_TASE_2024_3395325
crossref_primary_10_1007_s11071_023_08956_z
crossref_primary_10_1109_TASE_2023_3297235
crossref_primary_10_1016_j_chaos_2025_116145
crossref_primary_10_1016_j_engappai_2025_110485
crossref_primary_10_1002_rnc_7821
crossref_primary_10_1109_TCSII_2023_3310275
crossref_primary_10_1109_TASE_2023_3341801
crossref_primary_10_1109_TCYB_2024_3379389
crossref_primary_10_3390_electronics12132924
crossref_primary_10_1109_TCSI_2023_3334869
crossref_primary_10_1109_TFUZZ_2024_3357083
crossref_primary_10_1109_TCYB_2023_3336737
crossref_primary_10_1109_TMECH_2023_3314640
crossref_primary_10_1016_j_cnsns_2023_107689
crossref_primary_10_1109_TASE_2024_3446862
crossref_primary_10_1109_TSIPN_2024_3384814
crossref_primary_10_1080_00207179_2023_2285408
crossref_primary_10_1177_09596518241300685
crossref_primary_10_1109_TASE_2023_3344087
crossref_primary_10_1080_00207721_2023_2293482
crossref_primary_10_1109_TASE_2024_3420447
crossref_primary_10_1109_TSMC_2024_3405568
crossref_primary_10_1002_acs_3708
crossref_primary_10_1016_j_jfranklin_2025_107514
crossref_primary_10_1080_00207721_2023_2293483
crossref_primary_10_1109_TAI_2024_3353150
crossref_primary_10_1016_j_jfranklin_2023_03_054
Cites_doi 10.1016/j.ins.2021.08.062
10.1007/s11071-022-07459-7
10.1109/TFUZZ.2020.2982618
10.1002/rnc.6154
10.1080/00207721.2021.1943562
10.1016/S0167-6911(99)00059-6
10.1080/00207721.2020.1863503
10.1017/S0269888904000116
10.1080/00207721.2020.1831645
10.1016/j.physa.2019.123504
10.1016/j.isatra.2021.07.048
10.1109/TAC.2007.904277
10.1109/TNNLS.2016.2558195
10.1109/TCYB.2015.2456028
10.1016/j.neucom.2019.04.049
10.1109/TAC.2010.2042764
10.1016/j.automatica.2003.10.021
10.1016/j.automatica.2006.09.022
10.1016/j.automatica.2014.03.015
10.1016/j.automatica.2012.05.008
10.1109/TAC.2009.2015562
10.1109/ACC.2014.6858991
10.1016/j.neucom.2015.10.013
10.1016/j.automatica.2015.07.022
10.1109/TCSII.2022.3149886
10.1007/978-3-642-14435-6_7
10.1109/ACCESS.2018.2831228
10.1109/TNET.2022.3183862
10.1109/TAC.2011.2174666
10.1016/j.automatica.2017.06.008
10.1109/7.464346
10.1109/TAC.2004.832201
10.1002/acs.3283
10.1080/00207179.2017.1305510
10.1016/j.amc.2021.126330
10.1109/TASE.2015.2403261
10.1109/JPROC.2006.887293
10.1109/TCYB.2020.2970736
10.1016/j.amc.2020.125725
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023
DBID 97E
RIA
RIE
AAYXX
CITATION
7SC
7SP
7TB
8FD
FR3
JQ2
L7M
L~C
L~D
DOI 10.1109/TASE.2022.3184022
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005–Present
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Mechanical & Transportation Engineering Abstracts
Technology Research Database
Engineering Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Mechanical & Transportation Engineering Abstracts
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Engineering Research Database
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
DatabaseTitleList Technology Research Database

Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1558-3783
EndPage 1674
ExternalDocumentID 10_1109_TASE_2022_3184022
9810870
Genre orig-research
GrantInformation_xml – fundername: National Natural Science Foundation of China
  grantid: 61573069
  funderid: 10.13039/501100001809
– fundername: Eduction Committee Liaoning Province, China
  grantid: LJ2019002
GroupedDBID -~X
0R~
29I
4.4
5GY
5VS
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
AENEX
AETIX
AGQYO
AGSQL
AHBIQ
AIBXA
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
EBS
EJD
F5P
HZ~
H~9
IFIPE
IPLJI
JAVBF
LAI
M43
O9-
OCL
PQQKQ
RIA
RIE
RNS
AAYXX
CITATION
RIG
7SC
7SP
7TB
8FD
FR3
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c293t-99e7518b49b9f59f1603fcd42129530b73b08ef220364f2050a33aa604442c3b3
IEDL.DBID RIE
ISSN 1545-5955
IngestDate Mon Jun 30 06:32:22 EDT 2025
Tue Jul 01 02:56:32 EDT 2025
Thu Apr 24 22:55:33 EDT 2025
Wed Aug 27 02:25:49 EDT 2025
IsPeerReviewed false
IsScholarly true
Issue 3
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
https://doi.org/10.15223/policy-029
https://doi.org/10.15223/policy-037
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c293t-99e7518b49b9f59f1603fcd42129530b73b08ef220364f2050a33aa604442c3b3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0001-7120-4164
0000-0001-5712-9356
0000-0001-6498-5580
0000-0003-1480-1872
0000-0002-0717-1713
PQID 2831522184
PQPubID 27623
PageCount 12
ParticipantIDs ieee_primary_9810870
proquest_journals_2831522184
crossref_primary_10_1109_TASE_2022_3184022
crossref_citationtrail_10_1109_TASE_2022_3184022
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2023-07-01
PublicationDateYYYYMMDD 2023-07-01
PublicationDate_xml – month: 07
  year: 2023
  text: 2023-07-01
  day: 01
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle IEEE transactions on automation science and engineering
PublicationTitleAbbrev TASE
PublicationYear 2023
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref35
ref12
ref15
ref37
ref36
ref31
ref30
ref11
ref10
ref1
ref39
ref16
ref38
ma (ref2) 2010; 55
ref19
ref18
zhou (ref41) 2008
ref24
ren (ref17) 2021
ref23
ref45
chen (ref33) 2021
ref26
ref25
ref20
ref42
yan (ref32) 2021
ref22
ref44
ref21
ref43
ref28
ref27
ref29
ref8
ref7
cai (ref14) 2022
ref9
ref4
wang (ref34) 2021
ref3
ref6
ref5
ref40
References_xml – ident: ref11
  doi: 10.1016/j.ins.2021.08.062
– ident: ref27
  doi: 10.1007/s11071-022-07459-7
– ident: ref35
  doi: 10.1109/TFUZZ.2020.2982618
– ident: ref28
  doi: 10.1002/rnc.6154
– ident: ref37
  doi: 10.1080/00207721.2021.1943562
– ident: ref43
  doi: 10.1016/S0167-6911(99)00059-6
– year: 2022
  ident: ref14
  article-title: Decentralized backstepping control for interconnected systems with non-triangular structural uncertainties
  publication-title: IEEE Trans Autom Control
– ident: ref18
  doi: 10.1080/00207721.2020.1863503
– ident: ref5
  doi: 10.1017/S0269888904000116
– ident: ref19
  doi: 10.1080/00207721.2020.1831645
– year: 2021
  ident: ref32
  article-title: Robust formation control for nonlinear heterogeneous multiagent systems based on adaptive event-triggered strategy
  publication-title: IEEE Trans Autom Sci Eng
– ident: ref9
  doi: 10.1016/j.physa.2019.123504
– ident: ref13
  doi: 10.1016/j.isatra.2021.07.048
– ident: ref39
  doi: 10.1109/TAC.2007.904277
– ident: ref24
  doi: 10.1109/TNNLS.2016.2558195
– ident: ref25
  doi: 10.1109/TCYB.2015.2456028
– ident: ref15
  doi: 10.1016/j.neucom.2019.04.049
– volume: 55
  start-page: 1263
  year: 2010
  ident: ref2
  article-title: Necessary and sufficient conditions for consensusability of linear multi-agent systems
  publication-title: IEEE Trans Autom Control
  doi: 10.1109/TAC.2010.2042764
– ident: ref10
  doi: 10.1016/j.automatica.2003.10.021
– year: 2021
  ident: ref34
  article-title: Neural adaptive self-triggered control for uncertain nonlinear systems with input hysteresis
  publication-title: IEEE Trans Neural Netw Learn Syst
– ident: ref12
  doi: 10.1016/j.automatica.2006.09.022
– ident: ref44
  doi: 10.1016/j.automatica.2014.03.015
– ident: ref38
  doi: 10.1016/j.automatica.2012.05.008
– ident: ref42
  doi: 10.1109/TAC.2009.2015562
– ident: ref8
  doi: 10.1109/ACC.2014.6858991
– ident: ref7
  doi: 10.1016/j.neucom.2015.10.013
– year: 2008
  ident: ref41
  publication-title: Adaptive Backstepping Control of Uncertain Systems Nonsmooth Nonlinearities Interactions or Time-Variations
– ident: ref16
  doi: 10.1016/j.automatica.2015.07.022
– ident: ref21
  doi: 10.1109/TCSII.2022.3149886
– ident: ref6
  doi: 10.1007/978-3-642-14435-6_7
– ident: ref1
  doi: 10.1109/ACCESS.2018.2831228
– ident: ref31
  doi: 10.1109/TNET.2022.3183862
– ident: ref40
  doi: 10.1109/TAC.2011.2174666
– ident: ref26
  doi: 10.1016/j.automatica.2017.06.008
– start-page: 1
  year: 2021
  ident: ref33
  article-title: Adaptive self-triggered control for a nonlinear uncertain system based on neural observer
  publication-title: Int J Control
– ident: ref20
  doi: 10.1109/7.464346
– ident: ref23
  doi: 10.1109/TAC.2004.832201
– ident: ref45
  doi: 10.1002/acs.3283
– ident: ref36
  doi: 10.1080/00207179.2017.1305510
– year: 2021
  ident: ref17
  article-title: Prescribed performance bipartite consensus control for stochastic nonlinear multiagent systems under event-triggered strategy
  publication-title: IEEE Trans Cybern
– ident: ref29
  doi: 10.1016/j.amc.2021.126330
– ident: ref4
  doi: 10.1109/TASE.2015.2403261
– ident: ref3
  doi: 10.1109/JPROC.2006.887293
– ident: ref30
  doi: 10.1109/TCYB.2020.2970736
– ident: ref22
  doi: 10.1016/j.amc.2020.125725
SSID ssj0024890
Score 2.6078875
Snippet An adaptive neural bipartite tracking control approach is proposed for nonlinear multi-agent systems in this article. In contrast to previous results, it is...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1663
SubjectTerms Actuator failure
Actuators
Adaptive control
Adaptive systems
Backstepping
bipartite tracking control
Closed loops
Communication
Communications systems
Control systems design
Cooperative control
dead-zone constraints
Fault tolerance
Fault tolerant systems
fault-tolerant control
Feedback control
Multi-agent systems
Multiagent systems
Nonlinear control
Nonlinear systems
Nonlinearity
self-triggered
Strategy
Systems stability
Tracking control
Transmission efficiency
Transportation systems
Title Adaptive Neural Self-Triggered Bipartite Fault-Tolerant Control for Nonlinear MASs With Dead-Zone Constraints
URI https://ieeexplore.ieee.org/document/9810870
https://www.proquest.com/docview/2831522184
Volume 20
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NbxMxEB01PcEBWgoi0FY-cEI4cbzrsD6mJVFVqb0kFRGXlb0ZQ9WQRI1z4dd3xrsJn0K97WGstTRj-z3P-A3AO4s9Tmd5aao-ypwgsnTOOokUIKoKBBlcqvK97l_c5JdTM92DD7u3MIiYis-ww58plz9bVhu-KuvaoqcovlrQIuJWv9X6qatXpPsURgTSWGOaDGZP2e5kMB4SE9SaCCrxGa1_O4NSU5W_duJ0vIyew9V2YnVVyV1nE32n-vGHZuNjZ34AzxqcKQZ1YBzCHi5ewNNf1AeP4Ptg5la82wlW6CDjMc6DnBBd_8oNPMXZ7YrjKqIYuc08yslyjnSyRXFel7cLwrviupbacPfiajBei8-38Zv4RHEjvywXyJbr1IQirl_CzWg4Ob-QTfcFWREEiNJa5JSMz623wdjA_ahDNeMMsjWZ8h8zrwoMOmUyg1ZGuSxzrs8CdLrKfPYK9hf0q9cgPKEknffNzJiQa_SFdcbnwatQIOZZ0Qa19UdZNdLkPLl5mSiKsiW7sGQXlo0L2_B-N2RV63L8z_iIXbIzbLzRhuOt08tm5a5LglsEaZj4vvn3qLfwhFvO1yW7x7Af7zd4QsAk-tMUkQ-GW91c
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NbxMxEB2VcgAOfJWKQAEfOCGcOt51WB9DaRSgySVbUXFZ2ZsxVIQkapwLv54Z7yZ8CnHbw6zW0pv1vPGM3wA8t9jjcpaXpu6jzIkiS-esk0gOoupAlMGlLt9Jf3Sev7swF3vwcncXBhFT8xl2-THV8mfLesNHZce26Cnyr2twneK-0c1trR_KekU6UWFOII01pq1h9pQ9LgfTU8oFtaYUlTIarX-JQmmsyh97cQowwzsw3i6t6Sv50t1E362__aba-L9rvwu3W6YpBo1r3IM9XNyHWz_pDx7A18HMrXi_E6zRQcZTnAdZUsL-iUd4iteXK_asiGLoNvMoy-UcKbZFcdI0uAtivGLSiG24KzEeTNfiw2X8LN6Q58iPywWy5TqNoYjrB3A-PC1PRrKdvyBrIgFRWotclPG59TYYG3gidahnXEO2JlP-VeZVgUGnWmbQyiiXZc71WYJO15nPDmF_QZ96CMITT9J538yMCblGX1hnfB68CgVinhUdUFs8qroVJ-fFzauUpChbMYQVQ1i1EHbgxe6VVaPM8S_jA4ZkZ9ii0YGjLehV---uKyJcRGo49X3097eewY1ROT6rzt5O3j-GmzyAvmngPYL9eLXBJ0RTon-avPM7Pxjgpg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Adaptive+Neural+Self-Triggered+Bipartite+Fault-Tolerant+Control+for+Nonlinear+MASs+With+Dead-Zone+Constraints&rft.jtitle=IEEE+transactions+on+automation+science+and+engineering&rft.au=Cheng%2C+Fabin&rft.au=Liang%2C+Hongjing&rft.au=Wang%2C+Huanqing&rft.au=Zong%2C+Guangdeng&rft.date=2023-07-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.issn=1545-5955&rft.eissn=1558-3783&rft.volume=20&rft.issue=3&rft.spage=1663&rft_id=info:doi/10.1109%2FTASE.2022.3184022&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1545-5955&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1545-5955&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1545-5955&client=summon