Achieving improved stability for automatic voltage regulation with fractional-order PID plus double-derivative controller and mountain gazelle optimizer


Izci D., Abualigah L., CAN Ö., Andiç C., Ekinci S.

International Journal of Dynamics and Control, 2024 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s40435-023-01381-5
  • Dergi Adı: International Journal of Dynamics and Control
  • Derginin Tarandığı İndeksler: Scopus
  • Anahtar Kelimeler: Automatic voltage regulator, Evolutionary algorithms, FOPIDD2 controller, Mountain gazelle optimizer
  • Recep Tayyip Erdoğan Üniversitesi Adresli: Evet

Özet

The stability of voltage in a power system is a critical factor that impacts the system’s performance. Automatic voltage regulator system plays a vital role in maintaining stable voltage levels, ensuring efficient and reliable electricity delivery. However, this system may face challenges, such as oscillating transient response, steady-state errors, and load variations. To overcome these limitations, various control techniques have been proposed, with proportional–integral–derivative controllers being the most commonly used. However, this research aims to optimize the parameters of the fractional-order proportional–integral–derivative plus double-derivative (FOPIDD2) controller for the automatic voltage regulator system. The proposed controller’s six parameters are tuned using a novel evolutionary algorithm technique, the mountain gazelle optimizer, for the first time. The performance of the FOPIDD2 controller, tuned with mountain gazelle optimizer, is compared to that of other controllers which were optimized using different optimization techniques in the literature, as well as 13 studies with different controller approaches. The results demonstrate that the proposed mountain gazelle optimizer-based FOPIDD2 controller outperforms previously published optimization methods in the literature, leading to improvements in transient responses, such as settling time, rise time, and maximum overshoot. The implementation of the proposed approach is also demonstrated in a real-world setting and the robustness analysis is performed which further confirm the efficacy of the proposed approach.