In this study, it is ensured that the control of a simplified gas turbine power plant can be performed precisely with the fractional order proportional-integral-derivative (FOPID) controllers, which are the advanced form of conventional proportional-integral-derivative (PID) controllers. While conventional PID controllers contain three parameters, fractional order proportional-integral-derivative PID controllers contain five parameters. The large number of parameters allows more precise control to be made, but this makes difficult optimization of the controller. Since fractional order PID controllers are difficult to optimize with traditional mathematical methods; in this study, whale optimization algorithm (WOA), salp swarm algorithm (SSA), artificial bee colony (ABC) and atomic search optimization algorithm (ASO), which are among the nature-inspired (metaheuristic) optimization algorithms, are used. FOPID controller parameters which are optimized from four different nature-inspired algorithms are applied to the simplified gas turbine power plant model and the transient responses performances of the system output signals are compared. For this aim, settlement time and percentage maximum overshoot are used as comparison criteria. The simulation results show that the FOPID controller optimized with the artificial bee colony (ABC) algorithm performs better than the rest ofFOPIDcontrollers on the settling time and overshoot for this power plant model.
: April 26, 2021
|APA||Sezer, K , Bayhan, N . (2021). Doğadan Esinlenen Optimizasyon Algoritmaları Tabanlı Kesir Dereceli PID Denetleyicilerle Kontrol Edilen Bir Santral Modelinin Performansının İncelemesi . Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi , 8 (1) , 383-397 . DOI: 10.35193/bseufbd.928356|