About Structural Identifiability of Nonlinear Dynamic Systems under Uncertainty

1
Nikolay Karabutov
Nikolay Karabutov
1 MIREA-Russian Technological University

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Approach to the analysis of nonlinear dynamic systems structural identifiability (SI) under uncertainty is proposed. This approach has a difference from methods applied to SI estimation of dynamic systems in the parametrical space. Structural identifiability is interpreted as of the structural identification possibility a system nonlinear part. We show that the input should synchronize the system for the SI problem solution. The structural identifiability estimation method is based on the analysis of the framework special class. The input parameter effect on the possibility of the SI estimation of the system is studied.

21 Cites in Articles

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Nikolay Karabutov. 2018. \u201cAbout Structural Identifiability of Nonlinear Dynamic Systems under Uncertainty\u201d. Global Journal of Science Frontier Research - A: Physics & Space Science GJSFR-A Volume 18 (GJSFR Volume 18 Issue A11): .

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Issue Cover
GJSFR Volume 18 Issue A11
Pg. 51- 61
Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-A Classification: FOR Code: 020299
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v1.2

Issue date

November 22, 2018

Language

English

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Approach to the analysis of nonlinear dynamic systems structural identifiability (SI) under uncertainty is proposed. This approach has a difference from methods applied to SI estimation of dynamic systems in the parametrical space. Structural identifiability is interpreted as of the structural identification possibility a system nonlinear part. We show that the input should synchronize the system for the SI problem solution. The structural identifiability estimation method is based on the analysis of the framework special class. The input parameter effect on the possibility of the SI estimation of the system is studied.

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About Structural Identifiability of Nonlinear Dynamic Systems under Uncertainty

Nikolay Karabutov
Nikolay Karabutov MIREA-Russian Technological University

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