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Unknown input dynamic observer for a class of nonlinear systems using contraction analysis.

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Title: Unknown input dynamic observer for a class of nonlinear systems using contraction analysis.
Authors: Paul, Chayan Kumar1 (AUTHOR) chayanpaul007@gmail.com, Kar, Indra Narayan1 (AUTHOR), Sivaramakrishnan, Janardhanan1 (AUTHOR)
Source: International Journal of Systems Science. Jul2026, Vol. 57 Issue 10, p3183-3194. 12p.
Subjects: Nonlinear systems, Matrix inequalities, Robust control, Observability (Control theory)
Abstract: This paper proposes a novel methodology to design an unknown-input dynamic observer for a class of nonlinear systems, grounded in contraction theory. The primary contributions include a contraction-based framework for handling unknown inputs and the development of a dynamic observer structure that enhances robustness and steady-state accuracy. Existence and stability conditions are established using contraction analysis, ensuring exponential convergence of the estimation error. These conditions are further expressed as simplified linear matrix inequalities (LMIs), enabling computationally efficient implementation despite system nonlinearities. The proposed observer is evaluated against existing methods through numerical simulations, demonstrating improved performance and practical applicability in the presence of different unknown input. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Systems Science is the property of Taylor & Francis Ltd 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
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DbLabel: Engineering Source
An: 194673645
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
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  Data: Unknown input dynamic observer for a class of nonlinear systems using contraction analysis.
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  Data: <searchLink fieldCode="AR" term="%22Paul%2C+Chayan+Kumar%22">Paul, Chayan Kumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chayanpaul007@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kar%2C+Indra+Narayan%22">Kar, Indra Narayan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sivaramakrishnan%2C+Janardhanan%22">Sivaramakrishnan, Janardhanan</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Systems+Science%22">International Journal of Systems Science</searchLink>. Jul2026, Vol. 57 Issue 10, p3183-3194. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Nonlinear+systems%22">Nonlinear systems</searchLink><br /><searchLink fieldCode="DE" term="%22Matrix+inequalities%22">Matrix inequalities</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+control%22">Robust control</searchLink><br /><searchLink fieldCode="DE" term="%22Observability+%28Control+theory%29%22">Observability (Control theory)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper proposes a novel methodology to design an unknown-input dynamic observer for a class of nonlinear systems, grounded in contraction theory. The primary contributions include a contraction-based framework for handling unknown inputs and the development of a dynamic observer structure that enhances robustness and steady-state accuracy. Existence and stability conditions are established using contraction analysis, ensuring exponential convergence of the estimation error. These conditions are further expressed as simplified linear matrix inequalities (LMIs), enabling computationally efficient implementation despite system nonlinearities. The proposed observer is evaluated against existing methods through numerical simulations, demonstrating improved performance and practical applicability in the presence of different unknown input. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Systems Science is the property of Taylor & Francis Ltd 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.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/00207721.2025.2568715
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 3183
    Subjects:
      – SubjectFull: Nonlinear systems
        Type: general
      – SubjectFull: Matrix inequalities
        Type: general
      – SubjectFull: Robust control
        Type: general
      – SubjectFull: Observability (Control theory)
        Type: general
    Titles:
      – TitleFull: Unknown input dynamic observer for a class of nonlinear systems using contraction analysis.
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            NameFull: Paul, Chayan Kumar
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            NameFull: Kar, Indra Narayan
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            NameFull: Sivaramakrishnan, Janardhanan
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            – D: 15
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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              Value: 57
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              Value: 10
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            – TitleFull: International Journal of Systems Science
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