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Adaptive Active Disturbance Rejection Control of Solar Tracking Systems with Partially Known Model

Author

Listed:
  • Sergio Isai Palomino-Resendiz

    (Instituto Politécnico Nacional ESIME ZACATENCO, Ciudad de México 07738, Mexico
    These authors contributed equally to this work.)

  • Norma Beatriz Lozada-Castillo

    (Instituto Politécnico Nacional UPIITA, Ciudad de México 07340, Mexico
    These authors contributed equally to this work.)

  • Diego Alonso Flores-Hernández

    (Instituto Politécnico Nacional UPIITA, Ciudad de México 07340, Mexico
    These authors contributed equally to this work.)

  • Oscar Octavio Gutiérrez-Frías

    (Instituto Politécnico Nacional UPIITA, Ciudad de México 07340, Mexico
    These authors contributed equally to this work.)

  • Alberto Luviano-Juárez

    (Instituto Politécnico Nacional UPIITA, Ciudad de México 07340, Mexico
    These authors contributed equally to this work.)

Abstract

In this article, the trajectory tracking control of a solar tracking system is tackled by means of an adaptive active disturbance rejection control scheme. The state and disturbance estimation system is based on the combination of a time varying identification system and an adaptive observer. The stability and robustness of the controller is mathematically tested by means of the second method of Lyapunov, and its effectiveness is experimentally tested in a robotic test bed, achieving both lower energy consumption and better tracking results with respect to a PID-based controller.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2871-:d:677195
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    References listed on IDEAS

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    Cited by:

    1. 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.

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