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Cited by 16Control Systems and IdentificationMetaheuristic Optimization Algorithms ResearchAdvanced Control Systems Design

Identification of fractional order Wiener-Hammerstein systems based on adaptively fuzzy PSO and data filtering technique

Zong, Tiancheng, Li, Junhong, Lu, Guoping·2023·Applied Intelligence
DOI 10.1007/s10489-022-04220-w
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  • Zong et al. [34] demonstrated identification of fractional-order Wiener-Hammerstein-type nonlinear systems using fuzzy PSO, whereby a data filtering technique was applied prior to identification.

    “Recently, Zong et al. [34] demonstrated the identification of fractional-order Wiener-Hammerstein-type nonlinear systems using fuzzy PSO, whereby a data filtering technique was applied prior to identification.”

    From Application of Fractional Calculus for Parameter Estimation of Nonlinear Wiener Systems With Time Delay (2024) · cites this paper as [34]

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Authors
Zong, T., Li, J., & Lu, G.
Affiliations
Nantong University (CN)
Corresponding author
Li, Junhong
ORCID
Venue
Applied Intelligence
Publisher
Springer Science and Business Media LLC
Published
2022-10-21
Volume
53
Issue
11
Pages
14085-14101
ISSN
  • 0924-669X (ISSN-L)
  • 1573-7497
DOI
10.1007/s10489-022-04220-w
OpenAlex
W4307171687
Cited by
16
References
0
Citations by year
2026: 6 · 2025: 4 · 2024: 6
FWCI
1.01
Type
journal article
Language
en
Open access
closed
Licence
Locations
Applied Intelligence (publishedVersion)
Funders
  • National Natural Science Foundation of China (61973176, 62073180)
  • Six Talent Peaks Project in Jiangsu Province (XYDXX-038)
  • Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX21˙3083)
  • Natural Science Research Program of Jiangsu Colleges and Universities (20KJA470002)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
  • Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
  • Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Design
Keywords
system identification, parameter estimation, particle swarm optimization, data filtering, colored noise, moving average noise, fractional order estimation, nonlinear systems, adaptive learning factor

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