A hybrid symbiotic organisms search and simulated annealing technique applied to efficient design of PID controller for automatic voltage regulator


Celik E., ÖZTÜRK N.

SOFT COMPUTING, cilt.22, sa.23, ss.8011-8024, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 23
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/s00500-018-3432-2
  • Dergi Adı: SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.8011-8024
  • Anahtar Kelimeler: Automatic voltage regulator, PID controller, Optimization, Symbiotic organisms search algorithm, Simulated annealing, Hybridization, PERFORMANCE ANALYSIS, OPTIMIZATION, ALGORITHM, SYSTEM
  • Gazi Üniversitesi Adresli: Evet

Özet

This article is motivated by incorporating a hybrid symbiotic organisms search and simulated annealing (hSOS-SA) technique into efficient design of PID controller for automatic voltage regulator (AVR). Symbiotic organism search (SOS) algorithm is contemplated first to optimize parameters of PID controller using a new cost function which considers both time-domain and frequency-domain specifications. The excellence of SOS over some state-of-the-art techniques is confirmed through transient response analysis, root locus analysis and bode analysis for the identical AVR system. To fine-tune controller parameters for enhancing the system stability margin further, simulated annealing algorithm is invoked subsequently at the instant SOS has converged. Extensive numerical results computed from time and frequency response specifications affirm the superiority of proposed hSOS-SA algorithm such that after a minimal overshoot, hSOS-SA tuned AVR system settles to the step reference quickly and follows it with the least steady-state error. Such response is found to ensure a better stability margin than that using original SOS and earlier studies. Finally, robustness analysis is realized to verify that the designed controller is robust with regard to parameter uncertainties.