An Approach for DC Motor Speed Control with Off-Policy Reinforcement Learning Method
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Integration of self-learning mechanisms with control systems is frequently encountered in the literature due to the development of autonomous systems. This paper proposes a tuning method of PI controllers using a deep reinforcement learning algorithm, which is known as self-learning structure. The coefficients of the PI controller, which is used to control a DC motors, are determined. The proposed method aims to adjust the voltage value applied to the input of the DC motor to reach the desired speed with the tuned PI controller using the twin- delayed deep deterministic policy gradient (TD3) reinforcement learning algorithm. The Kp and Ki coefficients of the PI controller are taken as the absolute values of the neural network weights, which are driven by Gradient descent optimization to positive values with a fully connected layer. The proposed tuning method has been shown to provide a higher gain margin and a more optimal solution.
Açıklama
Anahtar Kelimeler
PI controller, Deep reinforcement learning, DC motor, Twin-delayed deep deterministic policy gradient
Kaynak
Balkan Journal of Electrical and Computer Engineering
WoS Q Değeri
Scopus Q Değeri
Cilt
11
Sayı
2
