ASM’nin MUS tabanlı hız-algılayıcısız öngörülü moment kontrolü

Öz

Bu çalışmada, asenkron motorların (ASM’lerin) yüksek başarımlı kontrolünü gerçekleştirmek için uyarlama mekanizmasında en küçük ortalama kareler (EKOK) algoritmasını kullanan modele uyarlamalı sisteme (MUS’a) dayanan hız-algılayıcısız öngörülü moment kontrol (ÖMK) tabanlı ASM sürücüsü tasarlanmıştır. Burada, EKOK uyarlamalı MUS ASM’nin stator akımları (i_sα ve i_sβ) tabanlıdır. Rotor akıları (φ_rα ve φ_rβ), rotor mekanik hızı (ω_m) ile birlikte i_sα ve i_sβ gerektiren akım model kullanılarak elde edilmiştir. Uyarlama mekanizmasında oransal-integral kullanan MUS tabanlı çalışmaların aksine, EKOK uyarlamalı MUS’da durum ve/veya parametreler her iterasyonda hesaplanan ve güncellenen ağırlık katsayıları olarak tanımlanabilir. Bu çalışmada ω_m her iterasyonda ağırlık katsayısı olarak kestirilir ve güncellenir. Ayrıca, EKOK uyarlamalı MUS geleneksel oransal-integrali kullanan MUS ile benzetim ortamında karşılaştırılmıştır. Benzetim sonuçları EKOK uyarlamasını kullanan stator akımları tabanlı MUS’un kestirim başarımını ve önerilen ÖMK tabanlı ASM sürücüsünün etkinliğini açıkça göstermektedir.

Anahtar Kelimeler

• Hız-algılayıcısız ASM kontrolü
• MÖK
• EKOK
• MUS

Speed-sensorless predictive torque control of the IM based on MRAS

Öz

In this study, an induction motor (IM) drive based on speed-sensorless predictive torque control (PTC) is designed to perform the high-performance control of the IMs by utilizing the least mean square (LMS) algorithm for the adaptation mechanism of the model reference adaptive system (MRAS). Here, the MRAS with LMS adaptation is based on the stator currents (i_sα and i_sβ) of the IM. Moreover, the rotor fluxes (φ_rα and φ_rβ) are obtained by the current model, which requires the rotor mechanical speed (ω_m) along with i_sα and i_sβ. In contrast to the other MRAS based studies using proportional-integral (PI) in the adaptation mechanisms to estimate state or parameter, it is possible to determine the states and/or parameters as weight coefficients in the MRAS with LMS adaptation which are calculated and updated in each iteration. Here, ω_m value is estimated and updated in each iteration as weight coefficient. Furthermore, the MRAS with LMS adaptation is compared to the MRAS using conventional PI in simulations. The simulation results clearly visualize both the estimation performance of stator current based MRAS using LMS adaptation and the effectiveness of the proposed PTC based IM drive.

Anahtar Kelimeler

• Speed-sensorless IM control
• PTC
• LMS algorithm
• MRAS
• Hız-algılayıcısız ASM kontrolü
• MÖK
• EKOK
• MUS

Kaynakça

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