Improving Zebra Optimization Algorithm via Fitness-Distance Balance Strategy: Application to AVR-LFC System

Ozturk O., ÇAVDAR B., Sahin E., AKYAZI Ö.

OPTIMAL CONTROL APPLICATIONS & METHODS, cilt.46, sa.6, ss.2771-2798, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Sayı: 6
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1002/oca.70028
  • Dergi Adı: OPTIMAL CONTROL APPLICATIONS & METHODS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2771-2798
  • Anahtar Kelimeler: AVR-LFC system control, fitness-distance balance, performance improvement of metaheuristic search algorithms, zebra optimization algorithm
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

This study proposes the FDB-ZOA algorithm, which is an improved version of the Zebra Optimization Algorithm (ZOA) with the Fitness-Distance Balance (FDB) strategy to enhance the exploration and exploitation balance. The developed algorithm was tested on CEC2020 benchmark functions and compared with 13 different state-of-the-art meta-heuristic algorithms, including ZOA. The comparisons were supported by mean success, standard deviation, box plots, convergence curves, and Wilcoxon and Friedman tests; FDB-ZOA demonstrated superior performance in all dimensions. Additionally, the algorithm's application potential has been demonstrated through parameter optimization of FOPID and FOPI-FOPD controllers in AVR-LFC systems, with results validated via time domain analysis, robustness tests, and OPAL-RT-based real-time simulations. The findings obtained indicate that FDB-ZOA is a strong candidate solution from both theoretical and practical perspectives.