A Spatial Learning-based Fault Tolerant Lateral Tracking Control for Autonomous Driving

In this paper, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical uncertainties, external disturbances as well as actuator failures. In order to facilitate the controller design, the uncertain vehicle dynamics...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on vehicular technology Ročník 72; číslo 10; s. 1 - 13
Hlavní autoři:	Li, Xuefang, Li, Hongbo, Meng, Deyuan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.10.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Actuator failure Actuators Adaptation models Adaptive control Algorithms Autonomous vehicles Control algorithms Control systems design Control theory Controllers Convergence Fault tolerance fault tolerant Feasibility studies lateral tracking Space vehicles Spatial adaptive iterative learning control Tracking control Uncertainty Vehicle dynamics
ISSN:	0018-9545, 1939-9359
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	In this paper, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical uncertainties, external disturbances as well as actuator failures. In order to facilitate the controller design, the uncertain vehicle dynamics are firstly transformed into a parametric form in the space domain, where the system uncertainties are reorganized and combined into the parametric and input distribution uncertainties. Furthermore, considering the under-actuated property of the vehicle dynamics, a novel technique in dealing with the non-square input distribution matrix is employed, in which a pseudo-like inverse matrix and a robust term are introduced into the controller to compensate the mismatch between the number of inputs and outputs. Then the proposed spatial learning-based fault tolerant control algorithm is developed, which is equipped with two adaptive parametric updating laws to estimate the parametric uncertainties and the multiplicative actuator faults correspondingly. Consequently, the convergence of the control algorithm is analyzed rigorously under the framework of composite energy function. Case studies verify the feasibility and effectiveness of the proposed control scheme.
AbstractList	In this article, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical uncertainties, external disturbances as well as actuator failures. In order to facilitate the controller design, the uncertain vehicle dynamics are firstly transformed into a parametric form in the space domain, where the system uncertainties are reorganized and combined into the parametric and input distribution uncertainties. Furthermore, considering the under-actuated property of the vehicle dynamics, a novel technique in dealing with the non-square input distribution matrix is employed, in which a pseudo-like inverse matrix and a robust term are introduced into the controller to compensate the mismatch between the number of inputs and outputs. Then the proposed spatial learning-based fault tolerant control algorithm is developed, which is equipped with two adaptive parametric updating laws to estimate the parametric uncertainties and the multiplicative actuator faults correspondingly. Consequently, the convergence of the control algorithm is analyzed rigorously under the framework of composite energy function. Case studies verify the feasibility and effectiveness of the proposed control scheme. In this paper, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical uncertainties, external disturbances as well as actuator failures. In order to facilitate the controller design, the uncertain vehicle dynamics are firstly transformed into a parametric form in the space domain, where the system uncertainties are reorganized and combined into the parametric and input distribution uncertainties. Furthermore, considering the under-actuated property of the vehicle dynamics, a novel technique in dealing with the non-square input distribution matrix is employed, in which a pseudo-like inverse matrix and a robust term are introduced into the controller to compensate the mismatch between the number of inputs and outputs. Then the proposed spatial learning-based fault tolerant control algorithm is developed, which is equipped with two adaptive parametric updating laws to estimate the parametric uncertainties and the multiplicative actuator faults correspondingly. Consequently, the convergence of the control algorithm is analyzed rigorously under the framework of composite energy function. Case studies verify the feasibility and effectiveness of the proposed control scheme.
Author	Li, Hongbo Li, Xuefang Meng, Deyuan
Author_xml	– sequence: 1 givenname: Xuefang orcidid: 0000-0003-3898-6509 surname: Li fullname: Li, Xuefang organization: School of Intelligent Systems Engineering, Sun Yat-Sen University, Guangzhou, China – sequence: 2 givenname: Hongbo surname: Li fullname: Li, Hongbo organization: School of Intelligent Systems Engineering, Sun Yat-Sen University, Guangzhou, China – sequence: 3 givenname: Deyuan orcidid: 0000-0002-0990-0166 surname: Meng fullname: Meng, Deyuan organization: Seventh Research Division, Beihang University (BUAA), Beijing, China
BookMark	eNp9kDFPwzAQhS1UJNrCzsBgiTnFdpzEHqtCASkSAwFG65I4KCW1i-0g8e9x1Q6IgenudO_d6X0zNDHWaIQuKVlQSuRN9VotGGHpImUFzwt2gqZUpjKRaSYnaEoIFYnMeHaGZt5v4si5pFP0tsTPOwg9DLjU4Exv3pMavG7xGsYh4MoO2oEJuIQQmwFXDpqPqMIra4KzA-6sw8sxWGO3dvT41vVfcX2OTjsYvL441jl6Wd9Vq4ekfLp_XC3LpGGShUS0QoiW1pC1eQdZXUCcRK6h4w0jtYCWtZzyQsqaN1rzgrWCS8lkDV0dU6ZzdH24u3P2c9Q-qI0dnYkvFROFyAhjeRpV5KBqnPXe6U7tXL8F960oUXt8KuJTe3zqiC9a8j-Wpg8R1D419MN_xquDsdda__pDWQyWpz-xgX9y
CODEN	ITVTAB
CitedBy_id	crossref_primary_10_1016_j_jfranklin_2025_107937 crossref_primary_10_1007_s11071_025_11320_y crossref_primary_10_1109_OJITS_2025_3583787 crossref_primary_10_1177_09544070251325911 crossref_primary_10_1109_JIOT_2025_3546962
Cites_doi	10.1109/TITS.2003.811644 10.1016/j.conengprac.2020.104654 10.1109/TCST.2007.894653 10.1016/j.automatica.2021.110024 10.1002/rnc.3601 10.1016/j.conengprac.2018.04.007 10.1109/TITS.2015.2486815 10.1016/j.automatica.2014.05.002 10.1016/j.automatica.2018.04.011 10.1109/TCST.2020.2971957 10.1109/TIV.2016.2578706 10.1109/TCST.2020.3024586 10.1007/s12239-020-0094-8 10.1002/rnc.3333 10.1007/978-1-4612-0571-5_4 10.1109/ACC.2016.7526680 10.1109/TRA.2003.819598 10.1109/TIE.2017.2739680 10.1109/TCST.2013.2245667 10.1109/TCST.2020.3006123 10.1109/MCI.2019.2901089 10.1109/DDCLS52934.2021.9455606 10.1109/TVT.2020.3014628 10.1109/TCST.2002.804120 10.1109/TCST.2014.2338354 10.1109/ACC.2015.7171151 10.1109/TNNLS.2021.3136644 10.1109/CDC42340.2020.9304347 10.1109/TCST.2020.3028219 10.1016/j.conengprac.2018.02.002 10.1016/j.jfranklin.2019.08.012 10.1007/s10846-016-0442-0 10.1109/TCST.2021.3089885 10.1016/j.ifacol.2017.08.049 10.1049/iet-its.2019.0411 10.1109/TITS.2015.2435016 10.1109/TCST.2021.3049958 10.1109/TSMC.2017.2712561 10.1109/TFUZZ.2017.2698370
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 7SP 8FD FR3 KR7 L7M
DOI	10.1109/TVT.2023.3274672
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998-Present IEEE Electronic Library (IEL) CrossRef Electronics & Communications Abstracts Technology Research Database Engineering Research Database Civil Engineering Abstracts Advanced Technologies Database with Aerospace
DatabaseTitle	CrossRef Civil Engineering Abstracts Engineering Research Database Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts
DatabaseTitleList	Civil Engineering Abstracts
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1939-9359
EndPage	13
ExternalDocumentID	10_1109_TVT_2023_3274672 10121866
Genre	orig-research
GrantInformation_xml	– fundername: Natural Science Foundation of China grantid: 62003376; 62273018 – fundername: Natural Science Foundation of Guangdong Province grantid: 2022A1515010881
GroupedDBID	-~X .DC 0R~ 29I 4.4 5GY 6IK 97E AAIKC AAJGR AAMNW AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACGFS ACIWK ACNCT AENEX AGQYO AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS HZ~ IFIPE IPLJI JAVBF LAI M43 MS~ O9- OCL P2P RIA RIE RNS RXW TAE TN5 3EH 5VS AAYXX AETIX AGSQL AI. AIBXA ALLEH CITATION EJD H~9 IAAWW IBMZZ ICLAB IFJZH VH1 7SP 8FD FR3 KR7 L7M
ID	FETCH-LOGICAL-c292t-8d888d1ba5d6fa5b7a8d186eaf4c20b8ad2d414799b4cee472d849929bafb6723
IEDL.DBID	RIE
ISICitedReferencesCount	8
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001098049700010&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0018-9545
IngestDate	Mon Jun 30 08:16:47 EDT 2025 Tue Nov 18 22:32:10 EST 2025 Sat Nov 29 02:59:08 EST 2025 Wed Aug 27 02:18:22 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	10
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-c292t-8d888d1ba5d6fa5b7a8d186eaf4c20b8ad2d414799b4cee472d849929bafb6723
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-0990-0166 0000-0003-3898-6509
PQID	2878502263
PQPubID	85454
PageCount	13
ParticipantIDs	crossref_primary_10_1109_TVT_2023_3274672 ieee_primary_10121866 proquest_journals_2878502263 crossref_citationtrail_10_1109_TVT_2023_3274672
PublicationCentury	2000
PublicationDate	2023-10-01
PublicationDateYYYYMMDD	2023-10-01
PublicationDate_xml	– month: 10 year: 2023 text: 2023-10-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE transactions on vehicular technology
PublicationTitleAbbrev	TVT
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 ref34 ref15 ref37 bartle (ref43) 2000; 2 ref14 ref31 ref30 bartle (ref40) 2014 ref11 ref33 ref10 ref32 xu (ref26) 2003; 291 ref2 ref1 ref17 ref39 jiang (ref7) 1997; 33 ref16 ref38 ref19 ref18 rajamani (ref36) 2011 ref24 ref23 ref25 ref20 ref42 ref41 ref22 ref44 ref21 ref28 ref27 ref29 ref8 ref9 ref4 ref3 ref6 ref5
References_xml	– ident: ref19 doi: 10.1109/TITS.2003.811644 – ident: ref12 doi: 10.1016/j.conengprac.2020.104654 – ident: ref13 doi: 10.1109/TCST.2007.894653 – ident: ref39 doi: 10.1016/j.automatica.2021.110024 – volume: 291 year: 2003 ident: ref26 publication-title: Linear and Nonlinear Iterative Learning Control – volume: 2 year: 2000 ident: ref43 publication-title: Introduction to Real Analysis – ident: ref16 doi: 10.1002/rnc.3601 – ident: ref37 doi: 10.1016/j.conengprac.2018.04.007 – ident: ref2 doi: 10.1109/TITS.2015.2486815 – ident: ref32 doi: 10.1016/j.automatica.2014.05.002 – ident: ref10 doi: 10.1016/j.automatica.2018.04.011 – ident: ref27 doi: 10.1109/TCST.2020.2971957 – ident: ref6 doi: 10.1109/TIV.2016.2578706 – ident: ref1 doi: 10.1109/TCST.2020.3024586 – ident: ref44 doi: 10.1007/s12239-020-0094-8 – ident: ref41 doi: 10.1002/rnc.3333 – ident: ref25 doi: 10.1007/978-1-4612-0571-5_4 – ident: ref11 doi: 10.1109/ACC.2016.7526680 – ident: ref9 doi: 10.1109/TRA.2003.819598 – ident: ref20 doi: 10.1109/TIE.2017.2739680 – ident: ref30 doi: 10.1109/TCST.2013.2245667 – ident: ref15 doi: 10.1109/TCST.2020.3006123 – volume: 33 start-page: 1393 year: 1997 ident: ref7 article-title: Tracking control of mobile robots: A case study in backstepping publication-title: Automatica – ident: ref24 doi: 10.1109/MCI.2019.2901089 – ident: ref34 doi: 10.1109/DDCLS52934.2021.9455606 – ident: ref23 doi: 10.1109/TVT.2020.3014628 – ident: ref8 doi: 10.1109/TCST.2002.804120 – ident: ref4 doi: 10.1109/TCST.2014.2338354 – ident: ref33 doi: 10.1109/ACC.2015.7171151 – ident: ref35 doi: 10.1109/TNNLS.2021.3136644 – ident: ref21 doi: 10.1109/CDC42340.2020.9304347 – ident: ref29 doi: 10.1109/TCST.2020.3028219 – ident: ref18 doi: 10.1016/j.conengprac.2018.02.002 – ident: ref42 doi: 10.1016/j.jfranklin.2019.08.012 – ident: ref5 doi: 10.1007/s10846-016-0442-0 – ident: ref28 doi: 10.1109/TCST.2021.3089885 – ident: ref14 doi: 10.1016/j.ifacol.2017.08.049 – ident: ref31 doi: 10.1049/iet-its.2019.0411 – ident: ref3 doi: 10.1109/TITS.2015.2435016 – ident: ref38 doi: 10.1109/TCST.2021.3049958 – ident: ref22 doi: 10.1109/TSMC.2017.2712561 – year: 2014 ident: ref40 publication-title: The Elements of Integration and Lebesgue Measure – year: 2011 ident: ref36 publication-title: Vehicle Dynamics and Control – ident: ref17 doi: 10.1109/TFUZZ.2017.2698370
SSID	ssj0014491
Score	2.4575713
Snippet	In this paper, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical... In this article, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	1
SubjectTerms	Actuator failure Actuators Adaptation models Adaptive control Algorithms Autonomous vehicles Control algorithms Control systems design Control theory Controllers Convergence Fault tolerance fault tolerant Feasibility studies lateral tracking Space vehicles Spatial adaptive iterative learning control Tracking control Uncertainty Vehicle dynamics
Title	A Spatial Learning-based Fault Tolerant Lateral Tracking Control for Autonomous Driving
URI	https://ieeexplore.ieee.org/document/10121866 https://www.proquest.com/docview/2878502263
Volume	72
WOSCitedRecordID	wos001098049700010&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1939-9359 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014491 issn: 0018-9545 databaseCode: RIE dateStart: 19670101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA86POjBz4nTKTl48dCtTdOkOY7p8DCGhzp3K_mqDMYqW-vfb5JmYyIKXkoLSSnvJX3v5b33-wFwz5IklbHSQVGEcYATjoM0KsxFK8o0k6hwwPPTMZ1M0tmMvfhmddcLo7V2xWe6Z29dLl-VsrZHZX2LRWUB2vbBPqWkadbapgww9vR4kdnBxi_Y5CRD1s-mWc_ShPdiZNk10Dcb5EhVfvyJnXkZnfzzw07Bsfcj4aBR_BnY08tzcLSDLngB3gbQEg6bBQY9iup7YI2WgiNeLyqYlQttLFUFx9y2IS-gsVvSnpzDYVO_Do1DCwd1ZfseynoNH1dze_zQBq-jp2z4HHgehUAihqogVSbMVZHgiSIFTwTl5iklmhdYolCkXCGFI0wZE9jYTEyRSk0ghJjghTDiii9Ba1ku9RWAmlNFCU9wTAiWhAsujLZjoROtCqlEB_Q3ks2lBxm3XBeL3AUbIcuNLnKri9zrogMetjM-GoCNP8a2rex3xjVi74DuRnu534Lr3ISCaWI8FBJf_zLtBhzatzeleV3Qqla1vgUH8rOar1d3bnV9AZLBzbs
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LS8NAEB60CurBZ8Vq1T148ZA23ewm2WOploq1eIjVW9hXpBBaaRN_v7tJWiqi4CUksEvCzG5mZmfm-wBuGKWh9JR2ksT1HEI5ccJOYi5aBUwziZMCeH48DEaj8O2NPVfN6kUvjNa6KD7TLXtb5PLVTOb2qKxtsagsQNsmbFFCsFu2a62SBoRUBHkds4eNZ7DMSrqsHY2jliUKb3nY8mvgb1aooFX58S8uDEz_4J-fdgj7lSeJuqXqj2BDT49hbw1f8AReu8hSDpslhioc1XfHmi2F-jxPMxTNUm1sVYaG3DYip8hYLmnPzlGvrGBHxqVF3TyznQ-zfIHu5hN7AFGHl_591Bs4FZOCIzHDmRMqE-iqjuBU-QmnIuDmKfQ1T4jErgi5wop0SMCYIMZqkgCr0IRCmAmeCCMu7xRq09lUnwHSPFCBzynxfJ9InwsujL49oalWiVSiAe2lZGNZwYxbtos0LsINl8VGF7HVRVzpogG3qxkfJcTGH2PrVvZr40qxN6C51F5cbcJFbILBkBofxffOf5l2DTuD6GkYDx9Gjxewa99UFuo1oZbNc30J2_IzmyzmV8VK-wJvStEC
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=A+Spatial+Learning-Based+Fault+Tolerant+Lateral+Tracking+Control+for+Autonomous+Driving&rft.jtitle=IEEE+transactions+on+vehicular+technology&rft.au=Li%2C+Xuefang&rft.au=Li%2C+Hongbo&rft.au=Meng%2C+Deyuan&rft.date=2023-10-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.issn=0018-9545&rft.eissn=1939-9359&rft.volume=72&rft.issue=10&rft.spage=12567&rft_id=info:doi/10.1109%2FTVT.2023.3274672&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0018-9545&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0018-9545&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0018-9545&client=summon