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Comparative Analysis of Fixed-Parameter and UKF-Based Adaptive M2PC-Controlled Induction Machines Under Parameter Variations    
Yazarlar (3)
Arş. Gör. Uğur Ufuk KÖRPE Arş. Gör. Uğur Ufuk KÖRPE
Kırşehir Ahi Evran Üniversitesi, Türkiye
Mustafa Gökdağ
Karabük Üniversitesi, Türkiye
Ozan Gülbudak
Karabük Üniversitesi, Türkiye
Devamını Göster
Özet
This paper presents a simulation-based comparative analysis of Modulated Model Predictive Control (M2PC) strategies under parameter variations in induction motors. Two control schemes are evaluated: one using fixed (nominal) parameters and another integrating an Unscented Kalman Filter (UKF) for online estimation of magnetizing inductance (Lm) and rotor resistance (Rr). Results have shown that parameter mismatch significantly affects electromagnetic torque production, flux regulation, and power quality, leading to performance degradation. The UKF-based controller effectively compensates for these deviations, maintaining accurate torque and flux control. These findings are particularly relevant for electric vehicle applications, where direct torque control is essential. In such systems, unaccounted parameter variations can lead to torque deficits and loss of drive accuracy. The study demonstrates that integrating UKF into model-based control enhances system robustness, efficiency, and torque delivery under dynamic conditions.
Anahtar Kelimeler
Induction machine | modulated model predictive control | parameter estimation | torque production | Unscented Kalman filter
Bildiri Türü Tebliğ/Bildiri
Bildiri Alt Türü Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum)
Bildiri Niteliği Alanında Hakemli Uluslararası Kongre/Sempozyum
Bildiri Dili İngilizce
Kongre Adı 2025 7th Global Power, Energy and Communication Conference (GPECOM)
Kongre Tarihi 11-06-2025 / 13-06-2025
Basıldığı Ülke Almanya
Basıldığı Şehir