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Fractional Systems’ Identification Based on Implicit Modulating Functions

Author

Listed:
  • Oliver Stark

    (Sartorius Stedim Bitech GmbH, 37099 Göttingen, Germany
    Faculty of Electrical Engineering and Information Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
    Faculty of Electrical Engineering and Information Technology, Institute of Control Systems (IRS), 76131 Karlsruhe, Germany)

  • Marius Eckert

    (Faculty of Electrical Engineering and Information Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
    Faculty of Electrical Engineering and Information Technology, Institute of Control Systems (IRS), 76131 Karlsruhe, Germany
    Robert Bosch GmbH, 70839 Gerlingen, Germany)

  • Albertus Johannes Malan

    (Faculty of Electrical Engineering and Information Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Sören Hohmann

    (Faculty of Electrical Engineering and Information Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

Abstract

This paper presents a new method for parameter identification based on the modulating function method for commensurable fractional-order models. The novelty of the method lies in the automatic determination of a specific modulating function by controlling a model-based auxiliary system, instead of applying and parameterizing a generic modulating function. The input signal of the model-based auxiliary system used to determine the modulating function is designed such that a separate identification of each individual parameter of the fractional-order model is enabled. This eliminates the shortcomings of the common modulating function method in which a modulating function must be adapted to the investigated system heuristically.

Suggested Citation

  • Oliver Stark & Marius Eckert & Albertus Johannes Malan & Sören Hohmann, 2022. "Fractional Systems’ Identification Based on Implicit Modulating Functions," Mathematics, MDPI, vol. 10(21), pages 1-24, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:21:p:4106-:d:962776
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    References listed on IDEAS

    as
    1. Singh, Jagdev, 2020. "Analysis of fractional blood alcohol model with composite fractional derivative," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Brian Ospina Agudelo & Walter Zamboni & Eric Monmasson, 2021. "A Comparison of Time-Domain Implementation Methods for Fractional-Order Battery Impedance Models," Energies, MDPI, vol. 14(15), pages 1-23, July.
    3. repec:taf:tsysxx:v:48:y:2017:i:7:p:1460-1471 is not listed on IDEAS
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