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Novel Adaptive Extended State Observer for Dynamic Parameter Identification with Asymptotic Convergence

Author

Listed:
  • Radosław Patelski

    (Institute of Automatic Control and Robotics, Poznan University of Technology, ul. Piotrowo 3a, 60-965 Poznan, Poland)

  • Dariusz Pazderski

    (Institute of Automatic Control and Robotics, Poznan University of Technology, ul. Piotrowo 3a, 60-965 Poznan, Poland)

Abstract

In this paper, a novel method of parameter identification of linear in parameter dynamic systems is presented. The proposed scheme employs an Extended State Observer to online estimate a state of the plant and momentary value of total disturbance present in the system. A notion is made that for properly redefined dynamics of the system, this estimate can be interpreted as a measure of modeling error caused by the parameter uncertainty. Under this notion, a disturbance estimate is used as a basis for classic gradient identification. A global convergence of both state and parameter estimates to their true values is proved using the Lyapunov approach under an assumption of a persistent excitation. Finally, results of simulation and experiments are presented to support the theoretical analysis. The experiments were conducted using a compliant manipulator joint and obtained results show the usefulness of the proposed method in drive control systems and robotics.

Suggested Citation

  • Radosław Patelski & Dariusz Pazderski, 2022. "Novel Adaptive Extended State Observer for Dynamic Parameter Identification with Asymptotic Convergence," Energies, MDPI, vol. 15(10), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3602-:d:815754
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    References listed on IDEAS

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    1. Sergio Isai Palomino-Resendiz & Norma Beatriz Lozada-Castillo & Diego Alonso Flores-Hernández & Oscar Octavio Gutiérrez-Frías & Alberto Luviano-Juárez, 2021. "Adaptive Active Disturbance Rejection Control of Solar Tracking Systems with Partially Known Model," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
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