Adaptive DC-output current regulation of basic series negative luo converter via uncertain dynamics: An interval type-2 PD-fuzzy logic control approach


Gani A., Sahin C.

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2025 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1177/01423312251361675
  • Dergi Adı: TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Kayseri Üniversitesi Adresli: Evet

Özet

This study aims to design a novel adaptive dc-output current regulator for a basic series negative output luo converter by means of an interval type-2 proportional + derivative fuzzy logic controller and to provide the desired transient response by using ellipsoid interval type-2 fuzzy membership functions with different uncertainty width ratios. In order to realize this aim, firstly, ellipsoid interval type-2 fuzzy membership functions with different uncertainty width ratios, which are closest to the human way of thinking, are selected. Then, the performances of these ellipsoid interval type-2 fuzzy membership functions with different uncertainty width ratios are adapted through the MacVicar-Whelan rule base to reduce the computational burden in terms of step dc-output current variation and step dc-input voltage variation using MATLAB/Simulink software. The dynamic performance of ellipsoid interval type-2 fuzzy membership functions with uncertain dynamics derived from different uncertainty width ratios were compared to each other and proportional + integral controller regarding three performance measures, namely rise time, settling time, and recovery time in detail. The simulation results demonstrated that the ellipsoid interval type-2 fuzzy membership function with a higher uncertainty width ratio (a1 = 1.6 and a2 = 0.4) improved average rise, settling and recovery time values by 68.59%, 76.24%, and 67.69%, respectively. Thus, it can be said that the ellipsoid interval type-2 fuzzy membership function with a higher uncertainty width ratio (a1 = 1.6 and a2 = 0.4) outperforms the proportional + integral controller and the other ellipsoid interval type-2 fuzzy membership functions with different uncertainty width ratios in terms of all performance measures.