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Experimental Investigation of an Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller for Buck DC/DC Converters

Author

Listed:
  • Badreddine Babes

    (Research Center in Industrial Technologies (CRTI), P.O. Box 64, Cheraga 16014, Algeria)

  • Noureddine Hamouda

    (Research Center in Industrial Technologies (CRTI), P.O. Box 64, Cheraga 16014, Algeria)

  • Fahad Albalawi

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Oualid Aissa

    (LPMRN Laboratory, Faculty of Sciences and Technology, University of Bordj Bou Arreridj, El Anseur 34000, Algeria)

  • Sherif S. M. Ghoneim

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Saad A. Mohamed Abdelwahab

    (Electrical Department, Faculty of Technology and Education, Suez University, Suez 43533, Egypt
    Department of Computers & Systems Engineering, High Institute of Electronic Engineering, Ministry of Higher Education, Bilbis-Sharqiya 44621, Egypt)

Abstract

This study proposes a way of designing a reliable voltage controller for buck DC/DC converter in which the terminal attractor approach is combined with an enhanced reaching law-based Fast Terminal Synergetic Controller (FTSC). The proposed scheme will overcome the chattering phenomena constraint of existing Sliding Mode Controllers (SMCs) and the issue related to the indefinite time convergence of traditional Synergetic Controllers (SCs). In this approach, the FTSC algorithm will ensure the proper tracking of the voltage while the enhanced reaching law will guarantee finite-time convergence. A Fuzzy Neural Network (FNN) structure is exploited here to approximate the unknown converter nonlinear dynamics due to changes in the input voltage and loads. The Fuzzy Neural Network (FNN) weights are adjusted according to the adaptive law in real-time to respond to changes in system uncertainties, enhancing the increasing the system’s robustness. The applicability of the proposed controller, i.e., the Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller (AFN-FTSC), is evaluated through comprehensive analyses in real-time platforms, along with rigorous comparative studies with an existing FTSC. A dSPACE ds1103 platform is used for the implementation of the proposed scheme. All results confirm fast reference tracking capability with low overshoots and robustness against disturbances while comparing with the FTSC.

Suggested Citation

  • Badreddine Babes & Noureddine Hamouda & Fahad Albalawi & Oualid Aissa & Sherif S. M. Ghoneim & Saad A. Mohamed Abdelwahab, 2022. "Experimental Investigation of an Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller for Buck DC/DC Converters," Sustainability, MDPI, vol. 14(13), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7967-:d:852175
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