PID Kontrolörün Kazanç Katsayılarının Optimizasyonu için Farklı Yöntemlerin Karşılaştırılması

Abstract

Proportional-Integral-Derivative (PID) controller is widely used in technical applications due to its robustness and ease of application. The gain values of a PID controller have a strong impact on performance criteria such as settling time, rise time, and overshoot. Systems that possess at least one of these criteria are considered strong control systems. Adjusting the parameters to obtain the best step response of closed loop control systems is a complex operation. While long known methods such as the Ziegler-Nichols (ZN) method were initially used to compute parameter values, today, metaheuristic algorithms are employed. This article focuses on the tuning of gain parameters of a PID controller using metaheuristic algorithms for the control of a system with a third-order transfer function. The proposed algorithms are Fuzzy Logic (FL), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). The comparison results concluded that GA is the best algorithm for optimization.