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Cited by 3Control Systems and IdentificationAdvanced Adaptive Filtering TechniquesAdvanced Control Systems Design

Parameter Estimation of Fractional Wiener Systems with the Application of Photovoltaic Cell Models

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Zhang, Ce, Meng, Xiangxiang, Ji, Yan·2023·Mathematics
DOI 10.3390/math11132945
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Abstract

Fractional differential equations are used to construct mathematical models and can describe the characteristics of real systems. In this paper, the parameter estimation problem of a fractional Wiener system is studied by designing linear filters which can obtain smaller tunable parameters and maintain the stability of the parameters in any case. To improve the identification performance of the stochastic gradient algorithm, this paper derives two modified stochastic gradient algorithms for the fractional nonlinear Wiener systems with colored noise. By introducing the forgetting factor, a forgetting factor stochastic gradient algorithm is deduced to improve the convergence rate. To achieve more efficient and accurate algorithms, we propose a multi-innovation forgetting factor stochastic gradient algorithm by means of the multi-innovation theory, which expands the scalar innovation into the innovation vector. To test the developed algorithms, a fractional-order dynamic photovoltaic model is employed in the simulation, and the dynamic elements of this photovoltaic model are estimated using the modified algorithms. Concurrently, a numerical example is given, and the simulation results verify the feasibility and effectiveness of the proposed procedures.

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  • The parameter identification method for the fractional order Wiener system [32] is applicable to the Wiener system with commensurate orders and without time delay.

    “The parameter identification method for the fractional order Wiener system was developed and validated on a photovoltaic cell in [32], which is applicable to the Wiener system with commensurate orders and without time delay.”

    From Application of Fractional Calculus for Parameter Estimation of Nonlinear Wiener Systems With Time Delay (2024) · cites this paper as [32]

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Cited by

Sorted by citations

Authors
Zhang, C., Meng, X., & Ji, Y.
Affiliations
  • Yantai Vocational College (CN)
  • Qingdao University of Science and Technology (CN)
Corresponding author
Zhang, Ce
ORCID
Venue
Mathematics
Publisher
MDPI AG
Published
2023-06-30
Volume
11
Issue
13
Pages
2945
ISSN
2227-7390 (ISSN-L)
DOI
10.3390/math11132945
OpenAlex
W4382940755
Cited by
3
References
0
Citations by year
2026: 1 · 2024: 1 · 2023: 1
FWCI
0.32
Type
journal article
Language
en
Open access
Licence
Locations
  • Mathematics (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (61472195, ZR2020MF160)
  • Natural Science Foundation of Shandong Province (61472195, ZR2020MF160)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
  • Physical Sciences › Engineering › Computational Mechanics › Advanced Adaptive Filtering Techniques
  • Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Design
Keywords
parameter estimation, stochastic gradient algorithm, forgetting factor, multi-innovation identification, colored noise, linear filters, convergence rate

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