Prescribed-Time Adaptive Parameter Estimation for Uncertain Linear Systems via Modified Volterra Operator

In this paper, a novel framework is developed to address the parameter estimation problem in uncertain linear systems. Primarily, a new modified Volterra operator is proposed by incorporating a delayed term into the standard Volterra operator. Several properties of the modified Volterra operator are...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Nonlinear dynamics Jg. 113; H. 21; S. 29337 - 29354
Hauptverfasser:	Shi, Shang, Min, Huifang, Hu, YinLong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.11.2025 Springer Nature B.V
Schlagworte:	Adaptive algorithms Applications of Nonlinear Dynamics and Chaos Theory Classical Mechanics Continuous time systems Control Control algorithms Design Dynamical Systems Initial conditions Kernel functions Linear systems Operators (mathematics) Parameter estimation Parameter identification Parameter modification Parameter uncertainty Physics Physics and Astronomy Robustness Statistical Physics and Dynamical Systems Vibration Linear system Uncertainties Delay Adaptive parameter estimation Prescribed time Volterra operator
ISSN:	0924-090X, 1573-269X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	In this paper, a novel framework is developed to address the parameter estimation problem in uncertain linear systems. Primarily, a new modified Volterra operator is proposed by incorporating a delayed term into the standard Volterra operator. Several properties of the modified Volterra operator are presented, illustrating that the proposed operator offers enhanced robustness against a wide range of uncertainties without requiring an increase in the order of the kernel functions. Building on the modified Volterra operator, we propose a novel adaptive estimation algorithm to achieve precise parameter estimation within a given prescribed time for continuous-time linear systems without uncertainties. Subsequent to this, a robustness analysis for systems subject to output uncertainties is provided. We present a sufficient condition under which the proposed robust estimation algorithm has been shown to achieve enhanced robustness against a wide range of uncertainties. The boundedness of the estimation error is guaranteed for uncertainties that satisfy this condition, including constant, slowly varying, and even some unbounded uncertainties. Additionally, our proposed parameter estimation algorithm only requires the availability of input and output signals, effectively eliminating dependency on unknown initial conditions and high-order derivatives of measurable signals. Finally, simulation comparison is presented to show the effectiveness of the proposed method.
AbstractList	In this paper, a novel framework is developed to address the parameter estimation problem in uncertain linear systems. Primarily, a new modified Volterra operator is proposed by incorporating a delayed term into the standard Volterra operator. Several properties of the modified Volterra operator are presented, illustrating that the proposed operator offers enhanced robustness against a wide range of uncertainties without requiring an increase in the order of the kernel functions. Building on the modified Volterra operator, we propose a novel adaptive estimation algorithm to achieve precise parameter estimation within a given prescribed time for continuous-time linear systems without uncertainties. Subsequent to this, a robustness analysis for systems subject to output uncertainties is provided. We present a sufficient condition under which the proposed robust estimation algorithm has been shown to achieve enhanced robustness against a wide range of uncertainties. The boundedness of the estimation error is guaranteed for uncertainties that satisfy this condition, including constant, slowly varying, and even some unbounded uncertainties. Additionally, our proposed parameter estimation algorithm only requires the availability of input and output signals, effectively eliminating dependency on unknown initial conditions and high-order derivatives of measurable signals. Finally, simulation comparison is presented to show the effectiveness of the proposed method.
Author	Min, Huifang Hu, YinLong Shi, Shang
Author_xml	– sequence: 1 givenname: Shang surname: Shi fullname: Shi, Shang organization: School of Internet of Things, Nanjing University of Posts and Telecommunications – sequence: 2 givenname: Huifang surname: Min fullname: Min, Huifang email: jiejie1043640772@126.com organization: School of Automation, Nanjing University of Science and Technology – sequence: 3 givenname: YinLong surname: Hu fullname: Hu, YinLong organization: College of Artificial Intelligence and Automation, Hohai University
BookMark	eNp9kM1KAzEURoNUsFZfwFXAdfQm0zQzSyn1ByoVrOIuxMytROyk3qSlfXujFdy5yuY755JzzHpd7JCxMwkXEsBcJinBSAFKCyl104jtAetLbSqhRs1Lj_WhUUMBDbwcseOU3gGgUlD3WXggTJ7CK7ZiHpbIr1q3ymGD_MGRW2JG4pOUw9LlEDu-iMSfOo-UXej4NHToiD_uUsZl4pvg-H1swyJgy5_jR2HJ8dkKyeVIJ-xw4T4Snv6-Aza_nszHt2I6u7kbX02FV0Zl4c1rq0bKVa4ZOmmGjVIeoQavVI1OVyNtPGiP2uDIO2O0Rj_UALUHJ6WpBux8r11R_FxjyvY9rqkrF22ldF2ExVBWar_yFFMiXNgVlT_Szkqw30XtvqgtRe1PUbstULWHUhl3b0h_6n-oL76tfFc
Cites_doi	10.1109/TAC.2022.3149964 10.1007/s11071-023-08868-y 10.1109/TAC.2017.2671343 10.1109/TIE.2024.3443954 10.1016/j.automatica.2024.111933 10.1177/01423312241262540 10.1016/j.enconman.2024.118866 10.1109/TAC.2019.2933388 10.23919/ECC.1999.7099355 10.1109/TAC.2011.2179869 10.1109/TAC.2008.919568 10.1016/j.automatica.2022.110485 10.1007/s11071-021-06462-8 10.1007/s11071-023-08623-3 10.1080/0020717031000149636 10.1007/s11071-023-08933-6 10.1007/978-3-642-21981-8 10.1016/j.automatica.2021.109559 10.1016/j.automatica.2017.06.008 10.1016/j.automatica.2016.10.031 10.23919/ECC57647.2023.10178290 10.1109/TAC.2020.3003651 10.1109/TSMC.2023.3240751 10.1007/BF02551284 10.1007/s11071-021-06859-5 10.1109/TAC.2021.3061645 10.1109/TAC.2022.3212005 10.1016/j.ejcon.2020.05.011 10.1121/1.399905 10.1016/j.automatica.2019.04.048 10.23919/ECC64448.2024.10590922 10.1016/j.automatica.2019.04.016 10.1109/TAC.2021.3130883 10.1016/j.media.2025.103537 10.1007/s11071-022-07820-w 10.1109/ACC.2016.7526771 10.1016/j.arcontrol.2020.06.002 10.1109/ACC.2013.6580311 10.1007/s11071-023-08304-1 10.1049/iet-cta.2010.0228 10.1109/TSMC.2024.3358350 10.1109/TAC.2019.2953146 10.1109/TAC.2022.3218592
ContentType	Journal Article
Copyright	The Author(s), under exclusive licence to Springer Nature B.V. 2025 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Nature B.V. 2025 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: The Author(s), under exclusive licence to Springer Nature B.V. 2025.
DBID	AAYXX CITATION
DOI	10.1007/s11071-025-11599-x
DatabaseName	CrossRef
DatabaseTitle	CrossRef
DatabaseTitleList
DeliveryMethod	fulltext_linktorsrc
Discipline	Applied Sciences Engineering Physics
EISSN	1573-269X
EndPage	29354
ExternalDocumentID	10_1007_s11071_025_11599_x
GrantInformation_xml	– fundername: Natural Science Foundation of Jiangsu Province grantid: BK20220943 funderid: http://dx.doi.org/10.13039/501100004608 – fundername: China Postdoctoral Science Foundation grantid: 2022M710682 – fundername: National Natural Science Foundation of China grantid: 62373135, 62203221, 62003131 funderid: http://dx.doi.org/10.13039/501100001809
GroupedDBID	-Y2 -~C -~X .86 .DC .VR 06D 0R~ 0VY 123 1N0 1SB 2.D 203 28- 29N 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 4.4 406 408 409 40D 40E 5QI 5VS 67Z 6NX 8FE 8FG 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAPKM AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBRH ABBXA ABDBE ABDZT ABECU ABFSG ABFTV ABHLI ABHQN ABJCF ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABRTQ ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACSNA ACSTC ACZOJ ADHHG ADHIR ADHKG ADIMF ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AEZWR AFBBN AFDZB AFEXP AFFNX AFGCZ AFHIU AFKRA AFLOW AFOHR AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGQPQ AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHPBZ AHSBF AHWEU AHYZX AIAKS AIGIU AIIXL AILAN AITGF AIXLP AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMVHM AMXSW AMYLF AMYQR AOCGG ARCEE ARMRJ ASPBG ATHPR AVWKF AXYYD AYFIA AYJHY AZFZN B-. BA0 BBWZM BDATZ BENPR BGLVJ BGNMA BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP EBLON EBS EIOEI EJD ESBYG F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ IWAJR IXC IXD IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KOW L6V LAK LLZTM M4Y M7S MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P2P P9T PF0 PHGZM PHGZT PQGLB PT4 PT5 PTHSS QOK QOS R4E R89 R9I RHV RNI RNS ROL RPX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCLPG SCV SDH SDM SEG SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TEORI TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WH7 WK8 YLTOR Z45 Z8Z ZMTXR ~A9 ~EX AAYXX AFFHD CITATION
ID	FETCH-LOGICAL-c272t-c7bd262a3a94a174922ce080c228ea53657c05ce57e6ca7755ec45008c0a1173
IEDL.DBID	RSV
ISICitedReferencesCount	0
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001530408900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0924-090X
IngestDate	Wed Nov 05 08:43:17 EST 2025 Sat Nov 29 07:13:13 EST 2025 Thu Oct 09 01:10:16 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	21
Keywords	Linear system Uncertainties Delay Adaptive parameter estimation Prescribed time Volterra operator
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c272t-c7bd262a3a94a174922ce080c228ea53657c05ce57e6ca7755ec45008c0a1173
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
PQID	3258749657
PQPubID	2043746
PageCount	18
ParticipantIDs	proquest_journals_3258749657 crossref_primary_10_1007_s11071_025_11599_x springer_journals_10_1007_s11071_025_11599_x
PublicationCentury	2000
PublicationDate	20251100 2025-11-00 20251101
PublicationDateYYYYMMDD	2025-11-01
PublicationDate_xml	– month: 11 year: 2025 text: 20251100
PublicationDecade	2020
PublicationPlace	Dordrecht
PublicationPlace_xml	– name: Dordrecht
PublicationSubtitle	An International Journal of Nonlinear Dynamics and Chaos in Engineering Systems
PublicationTitle	Nonlinear dynamics
PublicationTitleAbbrev	Nonlinear Dyn
PublicationYear	2025
Publisher	Springer Netherlands Springer Nature B.V
Publisher_xml	– name: Springer Netherlands – name: Springer Nature B.V
References	P Ge (11599_CR26) 2022; 68 V Adetola (11599_CR8) 2008; 53 Y Orlov (11599_CR34) 2022; 144 11599_CR18 CC Hua (11599_CR36) 2022; 67 G Pin (11599_CR24) 2017; 77 L Cui (11599_CR33) 2021; 106 B Yi (11599_CR11) 2022; 68 11599_CR21 11599_CR43 B Yi (11599_CR15) 2023; 111 11599_CR44 H Garnier (11599_CR5) 2003; 76 G Fedele (11599_CR20) 2018; 318 11599_CR25 H Min (11599_CR16) 2023; 68 11599_CR27 B Chen (11599_CR23) 2019; 106 W Zhai (11599_CR1) 2023; 111 11599_CR41 G Pin (11599_CR17) 2016; 61 11599_CR42 H Min (11599_CR29) 2025; 171 H Khalil (11599_CR39) 2002 R Kamalapurkar (11599_CR48) 2017; 62 M Krstic (11599_CR40) 1995 R Ortega (11599_CR45) 2020; 50 P Li (11599_CR22) 2020; 55 11599_CR6 M Bergamasco (11599_CR4) 2011; 5 11599_CR32 P Li (11599_CR19) 2020; 65 L Zhang (11599_CR35) 2022; 110 A Polyakov (11599_CR14) 2012; 57 W Consagra (11599_CR46) 2025; 102 P Young (11599_CR3) 2011 S Shi (11599_CR13) 2021; 127 Y Song (11599_CR28) 2017; 83 G Pin (11599_CR7) 2019; 107 11599_CR38 B Zhou (11599_CR37) 2021; 66 S Fang (11599_CR12) 2023; 111 I Karafyllis (11599_CR9) 2019; 65 T Zhang (11599_CR2) 2023; 111 R Ortega (11599_CR10) 2020; 66 11599_CR30 E Ozturk (11599_CR47) 2024; 319 11599_CR31
References_xml	– volume: 68 start-page: 1253 issue: 2 year: 2022 ident: 11599_CR11 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2022.3149964 – volume: 111 start-page: 19947 issue: 7 year: 2023 ident: 11599_CR12 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-023-08868-y – volume: 62 start-page: 3594 issue: 7 year: 2017 ident: 11599_CR48 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2017.2671343 – ident: 11599_CR30 doi: 10.1109/TIE.2024.3443954 – volume: 171 year: 2025 ident: 11599_CR29 publication-title: Automatica doi: 10.1016/j.automatica.2024.111933 – ident: 11599_CR27 doi: 10.1177/01423312241262540 – volume: 319 year: 2024 ident: 11599_CR47 publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2024.118866 – volume: 65 start-page: 2842 issue: 7 year: 2019 ident: 11599_CR9 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2019.2933388 – volume-title: Nonlinear and Adaptive Control Systems Design year: 1995 ident: 11599_CR40 – ident: 11599_CR6 doi: 10.23919/ECC.1999.7099355 – volume: 57 start-page: 2106 issue: 8 year: 2012 ident: 11599_CR14 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2011.2179869 – volume: 53 start-page: 807 issue: 3 year: 2008 ident: 11599_CR8 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2008.919568 – volume: 144 year: 2022 ident: 11599_CR34 publication-title: Automatica doi: 10.1016/j.automatica.2022.110485 – ident: 11599_CR38 doi: 10.1007/s11071-021-06462-8 – volume: 111 start-page: 15127 year: 2023 ident: 11599_CR2 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-023-08623-3 – volume: 76 start-page: 1337 issue: 13 year: 2003 ident: 11599_CR5 publication-title: Int. J. Control doi: 10.1080/0020717031000149636 – volume: 111 start-page: 21117 year: 2023 ident: 11599_CR1 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-023-08933-6 – volume-title: Recursive estimation and time-series analysis: An introduction for the student and practitioner year: 2011 ident: 11599_CR3 doi: 10.1007/978-3-642-21981-8 – volume: 127 year: 2021 ident: 11599_CR13 publication-title: Automatica doi: 10.1016/j.automatica.2021.109559 – volume: 83 start-page: 243 year: 2017 ident: 11599_CR28 publication-title: Automatica doi: 10.1016/j.automatica.2017.06.008 – volume: 77 start-page: 120 year: 2017 ident: 11599_CR24 publication-title: Automatica doi: 10.1016/j.automatica.2016.10.031 – ident: 11599_CR25 doi: 10.23919/ECC57647.2023.10178290 – volume: 66 start-page: 2265 issue: 5 year: 2020 ident: 11599_CR10 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2020.3003651 – ident: 11599_CR32 doi: 10.1109/TSMC.2023.3240751 – ident: 11599_CR42 doi: 10.1007/BF02551284 – ident: 11599_CR43 – volume: 106 start-page: 491 issue: 1 year: 2021 ident: 11599_CR33 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-021-06859-5 – volume: 66 start-page: 6123 issue: 12 year: 2021 ident: 11599_CR37 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2021.3061645 – volume: 68 start-page: 4932 issue: 8 year: 2022 ident: 11599_CR26 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2022.3212005 – volume: 55 start-page: 45 year: 2020 ident: 11599_CR22 publication-title: Eur. J. Control. doi: 10.1016/j.ejcon.2020.05.011 – ident: 11599_CR41 doi: 10.1121/1.399905 – volume: 107 start-page: 95 year: 2019 ident: 11599_CR7 publication-title: Automatic doi: 10.1016/j.automatica.2019.04.048 – ident: 11599_CR21 doi: 10.23919/ECC64448.2024.10590922 – volume: 106 start-page: 1 year: 2019 ident: 11599_CR23 publication-title: Automatica doi: 10.1016/j.automatica.2019.04.016 – volume: 67 start-page: 6159 issue: 11 year: 2022 ident: 11599_CR36 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2021.3130883 – volume: 102 year: 2025 ident: 11599_CR46 publication-title: Med. Image Anal. doi: 10.1016/j.media.2025.103537 – volume: 110 start-page: 3535 issue: 4 year: 2022 ident: 11599_CR35 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-022-07820-w – ident: 11599_CR44 doi: 10.1109/ACC.2016.7526771 – volume: 50 start-page: 278 year: 2020 ident: 11599_CR45 publication-title: Annu. Rev. Control. doi: 10.1016/j.arcontrol.2020.06.002 – volume: 61 start-page: 360 issue: 2 year: 2016 ident: 11599_CR17 publication-title: IEEE Trans. Autom. Control – ident: 11599_CR18 doi: 10.1109/ACC.2013.6580311 – volume: 111 start-page: 10049 issue: 7 year: 2023 ident: 11599_CR15 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-023-08304-1 – volume: 5 start-page: 856 issue: 7 year: 2011 ident: 11599_CR4 publication-title: IET Control Theory Appl. doi: 10.1049/iet-cta.2010.0228 – volume-title: Nonlinear systems year: 2002 ident: 11599_CR39 – ident: 11599_CR31 doi: 10.1109/TSMC.2024.3358350 – volume: 65 start-page: 3053 issue: 7 year: 2020 ident: 11599_CR19 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2019.2953146 – volume: 68 start-page: 5052 issue: 8 year: 2023 ident: 11599_CR16 publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2022.3218592 – volume: 318 start-page: 121 year: 2018 ident: 11599_CR20 publication-title: Appl. Math. Comput.
SSID	ssj0003208
Score	2.4431558
Snippet	In this paper, a novel framework is developed to address the parameter estimation problem in uncertain linear systems. Primarily, a new modified Volterra...
SourceID	proquest crossref springer
SourceType	Aggregation Database Index Database Publisher
StartPage	29337
SubjectTerms	Adaptive algorithms Applications of Nonlinear Dynamics and Chaos Theory Classical Mechanics Continuous time systems Control Control algorithms Design Dynamical Systems Initial conditions Kernel functions Linear systems Operators (mathematics) Parameter estimation Parameter identification Parameter modification Parameter uncertainty Physics Physics and Astronomy Robustness Statistical Physics and Dynamical Systems Vibration
Title	Prescribed-Time Adaptive Parameter Estimation for Uncertain Linear Systems via Modified Volterra Operator
URI	https://link.springer.com/article/10.1007/s11071-025-11599-x https://www.proquest.com/docview/3258749657
Volume	113
WOSCitedRecordID	wos001530408900001&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: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1573-269X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0003208 issn: 0924-090X databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT8MwDLbQAAkOPAaIwUA5cINIXdo07RGhIS48BAPtViVOJu2yTeuY-Pk4WcsAwQHOrZzKju3P9QvgTBkXSyMF1zbNeIKouEmjhCsjozRzqBFtWDah7u6yfj9_qJrCyrravU5JBku9bHajSIVCXyE5oZg854QcV8ndZV4dH59ePuxvLMIeuogiC_8Xol-1yvxM46s7WmLMb2nR4G2ut__3nTuwVaFLdrm4Druw4kZN2K6QJqv0uGzC5qcxhE1YD2WgWO7B0FdkkB0xznLfHMIurZ54g8getK_iIiGwLhmFRb8jI8DLnoliqCpgFNaS2rBqBjqbDzW7HdvhwB_9MvZZ-alm9xMXEvv70Lvu9q5ueLWMgaNQYsZRGStSoWOdJ5rCmFwIdAQ3UYjMaRmnUmEk0UnlUtRKSekwkYQwMNKdjooPoDEaj9whMEUoZCCsThRiEjljYmGkSbOBFYOoY5MWnNciKSaLkRvFcriyZ25BzC0Cc4u3FrRrqRWV-pVFLGSm_CR81YKLWkrLx79TO_rb68ewIRaC5lGnDY3Z9NWdwBrOZ8Nyehqu5TtTht5r
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dT9swED-hbmjsAVi3aR0d8wNvYClx4jh5rKYiptEOQUF9i-yzK_WlrZpS7c_f2U1WQOMBnhOdozvf3e9yXwAnyrhEGim4tlnOU0TFTRalXBkZZblDjWjDsgk1HObjcXFVN4VVTbV7k5IMlnrb7EaRCoW-QnJCMUXBCTm-Sclj-UK-65u7f_Y3EWEPXUSRhf8LMa5bZf5P47E72mLMJ2nR4G3OD173nYewX6NL1ttchw-w42ZtOKiRJqv1uGrD-wdjCNuwG8pAsfoIU1-RQXbEOMt9cwjrWb3wBpFdaV_FRUJgfTIKm35HRoCX3RLFUFXAKKwltWH1DHS2nmo2mNvpxB99N_dZ-aVmvxcuJPY_wei8P_pxwetlDByFEiuOyliRCZ3oItUUxhRCoCO4iULkTsskkwojiU4ql6FWSkqHqSSEgZGOY5V8htZsPnNfgClCIRNhdaoQ08gZkwgjTZZPrJhEsU07cNqIpFxsRm6U2-HKnrklMbcMzC3_dKDbSK2s1a8qEyFz5Sfhqw6cNVLaPn6e2teXvf4d3l2MBpfl5c_hryPYExuh8yjuQmu1vHff4C2uV9NqeRyu6F_Je-FP
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT-MwEB4hHis48OjuivL0YW9gkTpxnBwRUIGAUmkB9RbZY0fqpa3agvj5jJ2Usis4IM6J7GjGM_4mM98MwB9lXCyNFFzbNOMJouImjRKujIzSzKFGtGHYhOp0sl4v775j8Ydq91lKsuI0-C5Ng-nJyJYnc-IbRS0UBgvJCdHkOScUuZT4oUE-Xv_7-OaLYxFm0kUUZfg_Er2aNvPxGv9eTXO8-V-KNNw87Y3vf_MmrNeok51Wx2QLFtygARs1AmW1fU8asPauPWEDVkJ5KE5-Qt9XapB_Mc5yTxphp1aPvKNkXe2ru0g57IKcRcWDZASE2QOtGKoNGIW7ZE6s7o3Onvua3Q5tv_RbPw59tn6s2d3IhYT_L7hvX9yfXfJ6SANHocSUozJWpELHOk80hTe5EOgIhqIQmdMyTqXCSKKTyqWolZLSYSIJeWCkWy0V_4bFwXDgtoEpQielsDpRiEnkjImFkSbNSivKqGWTJhzN1FOMqlYcxbzpshduQcItgnCLlybszTRY1GY5KWIhM-U75KsmHM80Nn_8-Wo7X3v9EH50z9vFzVXnehdWRaVzHrX2YHE6fnL7sIzP0_5kfBBO6ysicuoz
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=Prescribed-Time+Adaptive+Parameter+Estimation+for+Uncertain+Linear+Systems+via+Modified+Volterra+Operator&rft.jtitle=Nonlinear+dynamics&rft.au=Shi%2C+Shang&rft.au=Min%2C+Huifang&rft.au=Hu%2C+YinLong&rft.date=2025-11-01&rft.pub=Springer+Netherlands&rft.issn=0924-090X&rft.eissn=1573-269X&rft.volume=113&rft.issue=21&rft.spage=29337&rft.epage=29354&rft_id=info:doi/10.1007%2Fs11071-025-11599-x&rft.externalDocID=10_1007_s11071_025_11599_x
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0924-090X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0924-090X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0924-090X&client=summon