Open AccessSpeed sensorless control strategy for six‐phase linear induction motor based on the dual reduced‐dimensional serial extended Kalman filters
Author(s) -
Sun Xingfa,
Nie Ziling,
Zhu Junjie,
Han Yi,
Sun Jun
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.6185
Subject(s) - control theory (sociology) , extended kalman filter , kalman filter , induction motor , computation , computer science , vector control , transformation (genetics) , invariant extended kalman filter , voltage , engineering , algorithm , control (management) , artificial intelligence , biochemistry , chemistry , electrical engineering , gene
This study proposes a speed sensorless vector control strategy for the six‐phase linear induction motor (SPLIM) based on the dual reduced‐dimensional serial extended Kalman filters (DRDSEKFs). Firstly, the low‐order mathematical model of SPLIM is obtained according to the equivalent transformation of primary voltage, current and flux components in the stationary coordinate system. Then, the state equation is derived and the speed estimation based on the five‐dimensional extended Kalman filter (EKF) is realised. To reduce the computation cost and improve the accuracy of speed estimation, a DRDSEKFs algorithm is proposed, with one two‐dimensional EKF and one three‐dimensional EKF operating serially in every control period. As the real‐time performance of the algorithm is guaranteed, it is possible to overcome the hysteretic nature of the traditional EKF and improve the dynamic estimation performance. Simulations and experiments show that the proposed sensorless control strategy is feasible and effective.