Improved speed and load torque estimations with adaptive fading extended Kalman filter
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, cilt.31, sa.1, 2021 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 31 Sayı: 1
- Basım Tarihi: 2021
- Doi Numarası: 10.1002/2050-7038.12684
- Dergi Adı: INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Anahtar Kelimeler: adaptive fading extended Kalman filter, induction motor, parameter estimation, speed‐, sensorless control, state estimation, SENSORLESS CONTROL, STABILITY, DRIVES
- Kayseri Üniversitesi Adresli: Hayır
Özet
Background Extended Kalman filter (EKF) is one of the most preferred observers for state and parameter estimation of induction motor. To achieve optimal estimations, EKFs require a stochastic system with complete dynamic or measurement equation. However, those equations are partially known in practice and may vary depending on operating conditions, leading to a degradation in the estimation performance of conventional EKFs (CEKFs).