Böbrek-ilhamlı Algoritma ile Ayarlanan PID Kontrolör Kullanarak DC Motor Hız Kontrolü

DC motor hız kontrol sistemlerinin birçok endüstriyel uygulamasında, çoğunlukla oransal-integral-türevsel (PID)kontrolörler kullanılmaktadır. Bu çalışmada, DC motor hız kontrolünün en uygun PID kontrolör parametreleri,yani oransal (Kp), integral (Ki) ve türev (Kd) kazançları, etkin ve hızlı bir ayar yöntemi olan böbrek-ilhamlıalgoritma (Kidney-inspired Algorithm - KA) ile belirlenmektedir. Kontrol sisteminin tasarımında, kontrolörparametrelerinin KA tarafından optimize edilebilmesi için zaman bölgesi tabanlı bir performans ölçütükullanılmıştır. Bu amaç fonksiyonu ile önerilen yaklaşımın performansını değerlendirmek için son yıllardayayımlanmış gri kurt optimizasyon (Grey Wolf Optimization - GWO) algoritması, istilacı ot optimizasyon(Invasive Weed Optimization – IWO) algoritması ve stokastik fraktal arama (Stochastic Fractal Search – SFS)algoritması gibi diğer modern sezgisel-üstü optimizasyon algoritmalarına dayalı yaklaşımlarla karşılaştırmalaryapılmıştır. Simülasyon sonuçlarından, DC motorun hız kontrolü için tasarlanan KA tabanlı PID (KA-PID)kontrolörün kapalı çevrim sisteminin aşım, yerleşme zamanı ve yükselme zamanı gibi sistem karakteristiklerini enaz iterasyonla önemli ölçüde iyileştirdiği görülmüştür. KA-PID kontrolör yaklaşımının gürbüzlük analizi de, DCmotor parametrelerindeki değişikliklerle gerçekleştirilmiştir.

Speed Control of DC Motor Using PID Controller Tuned via Kidneyinspired Algorithm

In many industrial applications of DC motor speed control systems, mostly proportional-integral-differential (PID) controllers are used. In this study, the optimal PID controller parameters that is proportional (Kp), integral (Ki) and differential (Kd) gains of DC motor speed control are determined by an effective and fast adjustment method, the kidney-inspired algorithm (KA). In the design of the control system, a time domain-based performance criterion was used to optimize the controller parameters by KA. In order to evaluate the performance of the proposed approach with this objective function, comparisons were made with approaches based on some modern metaheuristic optimization algorithms published in recent years such as grey wolf optimization (GWO), invasive weed optimization (IWO), and stochastic fractal search (SFS) algorithms. From the simulation results it has been shown that the KA-based PID (KA-PID) controller, which is designed for the speed control of the DC motor, has significantly improved the closed loop system characteristics such as overshoot, settling time, and rise time with minimal number of iterations. The robustness analysis of KA-PID controller approach has also been carried out with variations in the parameters of DC motor.

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