TY  - JOUR
T1  - Elektrohidrolik bir sistemin pekiştirmeli öğrenme tabanlı denetleyici ile konum denetiminin gerçekleştirilmesi
TT  - Reinforcement learning based position control of an electro-hydraulic system
AU  - Coşkun, Mustafa Yavuz
AU  - İtik, Mehmet
PY  - 2023
DA  - January
Y2  - 2022
DO  - 10.28948/ngumuh.1163241
JF  - Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi
JO  - NÖHÜ Müh. Bilim. Derg.
PB  - Nigde Omer Halisdemir University
WT  - DergiPark
SN  - 2564-6605
SP  - 280
EP  - 288
VL  - 12
IS  - 1
LA  - tr
AB  - Elektrohidrolik sistemler sağladıkları avantajlar sebebiyle endüstrinin vazgeçilmezi olmuştur. Buna karşın hidrolik sistemlerin doğrusal olmayan karakteristik özellikleri ve çok sayıda parametre belirsizliği barındırması bu sistemlerin denetimini zorlaştıran etmenler olarak öne çıkmaktadır. Bu çalışmada ise oransal valf ile sürülen asimetrik bir hidrolik pistonun konumu pekiştirmeli öğrenme ile denetlenmiştir. Pek çok pekiştirmeli öğrenme algoritması olmasına rağmen sürekli uzayda etkinliği ile öne çıkan derin deterministik politika gradyanı yöntemi tercih edilmiştir. İlgili hiper parametreler öncül çalışmalarla belirlenerek çoklu konum referans sinyali için denetleyicinin eğitimi benzetim ortamında gerçekleştirilmiştir. Elde edilen sonuçları kıyaslamak için aynı çalışma PID denetleyici ile de gerçekleştirilmiştir. Çalışmada kullanılan pekiştirmeli öğrenme yöntemi farklı karakteristiklere sahip konum referans sinyalinin takibinde PID denetleyiciden daha %25.51 oranında daha başarılı sonuçlar ortaya koymuştur.
KW  - Elektrohidrolik sistem
KW  - Modelleme
KW  - Konum denetimi
KW  - Pekiştirmeli öğrenme
KW  - Derin deterministik politika gradyanı
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UR  - https://doi.org/10.28948/ngumuh.1163241
L1  - https://dergipark.org.tr/en/download/article-file/2601268
ER  -