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Artificial intelligence-based controller for DC-Dc flyback converter

  • Muhammad Arslan Shahid
  • , Ghulam Abbas
  • , Mohammad Rashid Hussain
  • , Muhammad Usman Asad
  • , Umar Farooq
  • , Jason Gu
  • , Valentina E. Balas
  • , Muhammad Uzair
  • , Ahmed Bilal Awan
  • , Tanveer Yazdan
  • The University of Lahore
  • King Khalid University
  • Dalhousie University
  • University of the Punjab
  • Aurel Vlaicu University of Arad
  • Islamic University of Madinah
  • Majmaah University

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

This paper presents an intelligent voltage controller designed on the basis of an adaptive neuro-fuzzy inference system (ANFIS) for a flyback converter (FC) working in continuous conduction mode (CCM). The union of fuzzy logic (FL) and adaptive neural networks (ANN) makes ANFIS more robust against model parameters' uncertainties and perturbations in input voltage or load current. ANFIS inherits the advantages of structured knowledge representation from FL and learning capability from NN. Comparative analysis showed that the ANFIS controller offers not only the superior transient response characteristics, but also excellent steady-state characteristics compared to those of the FL controller (FLC) and proportional-integral-derivative (PID) controllers, thus validating its superiority over these traditional controllers. For this purpose,MATLAB/Simulink environment-based simulation results are presented for validation of the proposed converter compensated system under all operating conditions.

Original languageEnglish
Article number5108
JournalApplied Sciences (Switzerland)
Volume9
Issue number23
DOIs
StatePublished - 1 Dec 2019
Externally publishedYes

Keywords

  • ANFIS
  • Flyback converter (FC)
  • Fuzzy logic control (FLC)
  • PID
  • Robust

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