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Design of a Fuzzy Adaptive Voltage Controller for a Nonlinear Polymer Electrolyte Membrane Fuel Cell with an Unknown Dynamical System

Author

Listed:
  • Reza Ghasemi

    (Department of Electrical Engineering, University of Qom, Qom 3716146611, Iran)

  • Mehdi Sedighi

    (Department of Chemical Engineering, University of Qom, Qom 3716146611, Iran)

  • Mostafa Ghasemi

    (Chemical Engineering Section, Faculty of Engineering, Sohar University, Sohar 311, Oman)

  • Bita Sadat Ghazanfarpoor

    (Engineering Department, Islamic Azad University (IAU), Damavand Branch, Tehran 1477893855, Iran)

Abstract

This paper presents a fuzzy adaptive controller (FAC) for improving the efficiency and stability of fuel cells, assuming that the nonlinear dynamic model of the system is unknown. In polymer electrolyte membrane fuel cells, the output voltage should be controlled within a given interval. In contrast to prior studies that focused on designing controllers for known dynamical models of PEM fuel cells, the suggested approach addresses the real-world case of a PEM fuel cell with unknown dynamics. An intelligent technique is identified in the suggested strategy to approximate the state-space model of fuel cells to manage unknown functions. On an unknown model of fuel cells, traditional adaptive and fuzzy adaptive controllers are both implemented and compared. The main advantages of the proposed methodology are (1) stability of the closed-loop system using Lyapunov, (2) robustness against external disturbances, (3) application of the FAC to a PEM fuel cell, (4) convergence of the tracking error to 0, and (5) overcoming both unknown dynamics and uncertainty in the system. The most important and valuable advantages of the proposed system are its robustness, tracking error convergence, and Lyapunov stability. This manuscript aims to illustrate the responsiveness and fluency of the proposed procedure using a mathematical formulation of a multi-quadrotor system. As a result, the FAC is more efficient than the traditional one. To validate the controller performance, both the adaptive and fuzzy adaptive controllers are applied to a numerical model of a fuel cell and then compared.

Suggested Citation

  • Reza Ghasemi & Mehdi Sedighi & Mostafa Ghasemi & Bita Sadat Ghazanfarpoor, 2023. "Design of a Fuzzy Adaptive Voltage Controller for a Nonlinear Polymer Electrolyte Membrane Fuel Cell with an Unknown Dynamical System," Sustainability, MDPI, vol. 15(18), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13609-:d:1238061
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    References listed on IDEAS

    as
    1. Mojtaba Sedighi & Majid Mohammadi & Saeed Farahani Fard & Mehdi Sedighi, 2019. "The Nexus between Stock Returns of Oil Companies and Oil Price Fluctuations after Heavy Oil Upgrading: Toward Theoretical Progress," Economies, MDPI, vol. 7(3), pages 1-17, July.
    2. Mahmoud S. AbouOmar & Hua-Jun Zhang & Yi-Xin Su, 2019. "Fractional Order Fuzzy PID Control of Automotive PEM Fuel Cell Air Feed System Using Neural Network Optimization Algorithm," Energies, MDPI, vol. 12(8), pages 1-23, April.
    3. Feng Han & Ying Tian & Qiang Zou & Xin Zhang, 2020. "Research on the Fault Diagnosis of a Polymer Electrolyte Membrane Fuel Cell System," Energies, MDPI, vol. 13(10), pages 1-18, May.
    4. Robert Nebeluk & Maciej Ławryńczuk, 2022. "Fast Model Predictive Control of PEM Fuel Cell System Using the L 1 Norm," Energies, MDPI, vol. 15(14), pages 1-17, July.
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