View in EDS

Iteration‐Varying Fault Estimation for Nonlinear Distributed Parameter Systems via Open‐closed‐Loop Iterative Learning.

Saved in:
Bibliographic Details
Title: Iteration‐Varying Fault Estimation for Nonlinear Distributed Parameter Systems via Open‐closed‐Loop Iterative Learning.
Authors: Du, Kenan1 (AUTHOR), Lu, Haoran2 (AUTHOR), Chai, Yi1 (AUTHOR) chaiyi@cqu.edu.cn, Feng, Li3 (AUTHOR), Xu, Shuiqing4 (AUTHOR)
Source: International Journal of Robust & Nonlinear Control. Aug2026, Vol. 36 Issue 12, p6164-6174. 11p.
Subjects: Distributed parameter systems, Iterative learning control, Observability (Control theory)
Abstract: The issue discussed in this article is iteration‐varying fault estimation for nonlinear distributed parameter systems (DPSs), where faults exhibit iteration‐varying characteristics across iterative processes. Firstly, an iterative learning observer is designed for nonlinear DPSs. Secondly, a fault estimator is proposed under open‐closed‐loop iterative learning framework. The iterative learning mechanism and current feedback are integrated to tackle the challenges posed by iteration‐varying faults. Theoretical analysis using λ$$ \lambda $$‐norm and L2$$ {L}^2 $$ norm techniques prove the ultimate boundedness of fault estimation error. Lastly, the efficacy of proposed method is demonstrated via comprehensive simulations. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Robust & Nonlinear Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 195155239
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Iteration‐Varying Fault Estimation for Nonlinear Distributed Parameter Systems via Open‐closed‐Loop Iterative Learning.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Du%2C+Kenan%22">Du, Kenan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Haoran%22">Lu, Haoran</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chai%2C+Yi%22">Chai, Yi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chaiyi@cqu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Feng%2C+Li%22">Feng, Li</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Shuiqing%22">Xu, Shuiqing</searchLink><relatesTo>4</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Robust+%26+Nonlinear+Control%22">International Journal of Robust & Nonlinear Control</searchLink>. Aug2026, Vol. 36 Issue 12, p6164-6174. 11p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Distributed+parameter+systems%22">Distributed parameter systems</searchLink><br /><searchLink fieldCode="DE" term="%22Iterative+learning+control%22">Iterative learning control</searchLink><br /><searchLink fieldCode="DE" term="%22Observability+%28Control+theory%29%22">Observability (Control theory)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The issue discussed in this article is iteration‐varying fault estimation for nonlinear distributed parameter systems (DPSs), where faults exhibit iteration‐varying characteristics across iterative processes. Firstly, an iterative learning observer is designed for nonlinear DPSs. Secondly, a fault estimator is proposed under open‐closed‐loop iterative learning framework. The iterative learning mechanism and current feedback are integrated to tackle the challenges posed by iteration‐varying faults. Theoretical analysis using λ$$ \lambda $$‐norm and L2$$ {L}^2 $$ norm techniques prove the ultimate boundedness of fault estimation error. Lastly, the efficacy of proposed method is demonstrated via comprehensive simulations. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Robust & Nonlinear Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=195155239
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/rnc.70577
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 6164
    Subjects:
      – SubjectFull: Distributed parameter systems
        Type: general
      – SubjectFull: Iterative learning control
        Type: general
      – SubjectFull: Observability (Control theory)
        Type: general
    Titles:
      – TitleFull: Iteration‐Varying Fault Estimation for Nonlinear Distributed Parameter Systems via Open‐closed‐Loop Iterative Learning.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Du, Kenan
      – PersonEntity:
          Name:
            NameFull: Lu, Haoran
      – PersonEntity:
          Name:
            NameFull: Chai, Yi
      – PersonEntity:
          Name:
            NameFull: Feng, Li
      – PersonEntity:
          Name:
            NameFull: Xu, Shuiqing
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 08
              Text: Aug2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 10498923
          Numbering:
            – Type: volume
              Value: 36
            – Type: issue
              Value: 12
          Titles:
            – TitleFull: International Journal of Robust & Nonlinear Control
              Type: main
ResultId 1