Bulanık ayarlamaya dayalı adaptif PID ile fırçasız doğru akım motorlarının kontrolü
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Dosyalar
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Selçuk Üniversitesi, Fen Bilimleri Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Küçük hacimlere sahip olan fırçasız DA (FDA) motorlar verimlerinin ve torklarının yüksek olması nedeniyle havacılık sanayinden endüstriyel uygulamalara kadar birçok alanda yaygın olarak kullanılmaktadır. Teknolojinin gelişmesine paralel olarak FDA motor (FDAM) kontrol stratejilerinin gelişmesi ve kontrol maliyetlerinin düşmesiyle kullanım alanı da genişleyerek devam etmektedir. Bu tez çalışmasında rotor hızında referans hıza göre gözlemlenen değişimlerin asgari düzeye indirgenmesi amaçlanmıştır. Bunu gerçekleştirmek için oluşan hata değeri referans alınarak bulanık kontrol teknikleriyle PID parametreleri eş zamanlı olarak değiştirilmeye çalışılmıştır. FDA motora ait kontrol sistemi MATLAB/Simulink ortamında tasarlanmıştır. Simülasyon aynı özelliklere sahip iki motor üzerinde klasik PID ile bulanık ayarlamaya dayalı adaptif PID için farklı hızlarda çalışma kararlılıkları karşılaştırılmıştır. Simülasyonlar, 1000rpm ile 3000rpm arasında 5 adımda ve değişken hız rejimleri için gerçekleştirilmiştir. Sonuç olarak; en büyük iyileştirme 3000 devirde gerçekleştirilmiş olup klasik PID ile kontrol edilen sistemin yerleşme süresi 1,22 sn olmasına rağmen bulanık ayarlamaya dayalı adaptif PID kullanıldığında bu sürenin 0,167 saniye olduğu bulunmuştur. Maksimum aşım yüzdesi klasik PID için %5.4 iken bulanık ayarlamaya dayalı adaptif PID için % 0.096'ya düşmüştür. Kararlı durum hatası da 11 rpm'den 8 rmp'e inmiştir. Yumuşak kalkışlı bir sistemde hızın bulanık ayarlamaya dayalı adaptif PID ve klasik PID'nin sırasıyla yüksek hızlarda %0.059, %0,4 gibi, düşük hızlarda (96.8rpm) %0.83, %17.39 gibi hata seviyelerinde çalıştıkları gözlemlenmiştir. Yapılan araştırmanın sonucunda bulanık mantık tabanlı katsayıları güncellenen PID kontrollü motorun klasik PID kontrollü motora göre rotorunda gözlemlenen hızın referans hıza bağlı düzeltmenin daha kararlı olduğu, referans değeri için aşma yüzdesinin daha düşük olduğu sonucuna ulaşılmıştır.
Brushless DC (BLDC) motors, which have small volumes, are widely used in many areas from the aviation industry to industrial applications due to their high efficiency and torque. In parallel with the development of technology, the field of use continues to expand with the development of BLDC motor (BLDCM) control strategies and the decrease in control costs. In this thesis study, it is aimed to minimize the observed changes in rotor speed compared to the reference speed. To achieve this, PID parameters were tried to be changed simultaneously with fuzzy control techniques, taking the error value as a reference. The control system of the BLDC motor was designed in the MATLAB/Simulink environment. In the simulation, the operating stability of classical PID and adaptive PID based on fuzzy tuning was compared on two motors with the same features, at different speeds. Simulations were carried out in 5 steps and for variable speed regimes between 1000rpm and 3000rpm. In conclusion; the biggest improvement was achieved at 3000 rpm, and although the settling time of the classical PID controlled system was 1.22 seconds, it was found that this time was 0.167 seconds when the adaptive PID based on fuzzy tuning was used. While the maximum overshoot percentage was 5.4% for the classical PID, it decreased to 0.096% for the adaptive PID based on fuzzy tuning. Steady state error also decreased from 11 rpm to 8 rpm. In a soft start system, it has been observed that PID and classical PID, whose fuzzy-based speed parameters are updated, operate at error levels of 0.059%, 0.4% at high speeds, and 0.83% and 17.39% at low speeds (96.8rpm), respectively. As a result of the research, it was concluded that the correction of the speed observed in the rotor of the PID controlled motor, whose fuzzy logic-based coefficients were updated, based on the reference speed was more stable and the percentage of exceedance for the reference value was lower, compared to the classical PID controlled motor.
Brushless DC (BLDC) motors, which have small volumes, are widely used in many areas from the aviation industry to industrial applications due to their high efficiency and torque. In parallel with the development of technology, the field of use continues to expand with the development of BLDC motor (BLDCM) control strategies and the decrease in control costs. In this thesis study, it is aimed to minimize the observed changes in rotor speed compared to the reference speed. To achieve this, PID parameters were tried to be changed simultaneously with fuzzy control techniques, taking the error value as a reference. The control system of the BLDC motor was designed in the MATLAB/Simulink environment. In the simulation, the operating stability of classical PID and adaptive PID based on fuzzy tuning was compared on two motors with the same features, at different speeds. Simulations were carried out in 5 steps and for variable speed regimes between 1000rpm and 3000rpm. In conclusion; the biggest improvement was achieved at 3000 rpm, and although the settling time of the classical PID controlled system was 1.22 seconds, it was found that this time was 0.167 seconds when the adaptive PID based on fuzzy tuning was used. While the maximum overshoot percentage was 5.4% for the classical PID, it decreased to 0.096% for the adaptive PID based on fuzzy tuning. Steady state error also decreased from 11 rpm to 8 rpm. In a soft start system, it has been observed that PID and classical PID, whose fuzzy-based speed parameters are updated, operate at error levels of 0.059%, 0.4% at high speeds, and 0.83% and 17.39% at low speeds (96.8rpm), respectively. As a result of the research, it was concluded that the correction of the speed observed in the rotor of the PID controlled motor, whose fuzzy logic-based coefficients were updated, based on the reference speed was more stable and the percentage of exceedance for the reference value was lower, compared to the classical PID controlled motor.
Açıklama
Anahtar Kelimeler
Bulanık, Bulanık Kontrol, Bulanık Parametreli PID, FDAM, FDAM Kontrol, PID, BLDC, BLDC Control, Fuzzy, Fuzzy Control, Self-Tuning PID with Fuzzy
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Güntay S., (2024). Bulanık Ayarlamaya Dayalı Adaptif Pıd ile Fırçasız Doğru Akım Motorlarının Kontrolü. (Yüksek Lisans Tezi). Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Konya.
