Fractional Order PID Design based on Novel Improved Slime Mould Algorithm

İZCİ D., EKİNCİ S., Zeynelgil H. L., Hedley J.

ELECTRIC POWER COMPONENTS AND SYSTEMS, cilt.49, ss.901-918, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/15325008.2022.2049650
  • Dergi Adı: ELECTRIC POWER COMPONENTS AND SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Environment Index, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.901-918
  • Anahtar Kelimeler: slime mold algorithm, simulated annealing, opposition-based learning, FOPID controller, DC motor, automatic voltage regulator, STOCHASTIC FRACTAL SEARCH, OPTIMIZATION ALGORITHM, CONTROLLER, SYSTEM
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

This study attempts to maintain the terminal voltage level of an automatic voltage regulator (AVR) and control the speed of a direct current (DC) motor using a fractional order proportional integral derivative (FOPID) controller. The best parameters of the controller have been adjusted using a novel meta-heuristic algorithm called opposition-based hybrid slime mold with simulated annealing algorithm. The proposed algorithm aims to improve the original slime mold algorithm in terms of exploitation and exploration using simulated annealing and opposition-based learning, respectively. A time domain objective function was adopted as performance index to design the FOPID-based AVR and DC motor systems. The initial performance evaluation was carried out using unimodal and multimodal benchmark functions. The results confirmed the superior exploration and exploitation capabilities of the developed algorithm compared to the other state-of-the-art optimization algorithms. The performance of the proposed algorithm has also been assessed through statistical tests, time domain and frequency domain simulations along with robustness and disturbance rejection analyses for both DC motor and AVR systems. The proposed algorithm has shown superior capabilities for the respective systems compared to the other state-of-the-art optimization algorithms used for the same purpose.