Comparison of Metaheuristic Algorithm Performances for Optimization of Fractional Order PID Controllers Applied to Gas Turbine Power Plant
Nowadays, the use of metaheuristic optimization algorithms is becoming widespread because of easy applying and be able to provide requirements in the solution of high level complex optimization problems. In this study, four different metaheuristic optimization algorithms (particle swarm optimization, artificial bee colony, gray wolf optimization, moth-flame optimization) are used for the optimization of the fractional order PID (FOPID) controller applied to the gas turbine power plant model, which is considered as the sample model, and the transient responses of the optimized systems compared according to the system output signals. The settling time, maximum overshoot percentage and rise time are used as comparison criteria, and then it is concluded that the grey wolf optimization and artificial bee colony algorithms provided superior results with respect to the other algorithms discussed. By using metaheuristic algorithms, the optimization of the fractional order PID controller applied to the gas turbine power plant model has been achieved.
Copyright (c) 2021 Journal of Aeronautics and Space Technologies
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The manuscript with title and authors is being submitted for publication in Journal of Aeronautics and Space Technologies. This article or a major portion of it was not published, not accepted and not submitted for publication elsewhere. If accepted for publication, I hereby grant the unlimited and all copyright privileges to Journal of Aeronautics and Space Technologies.
I declare that I am the responsible writer on behalf of all authors.