Open AccessHybrid flux predictor‐based predictive flux control of permanent magnet synchronous motor drives
Author(s) -
Fu Rong,
Cao Yang
Publication year - 2022
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/elp2.12168
Subject(s) - control theory (sociology) , stator , model predictive control , vector control , direct torque control , torque , robustness (evolution) , flux (metallurgy) , engineering , computer science , voltage , control engineering , induction motor , physics , control (management) , materials science , artificial intelligence , mechanical engineering , biochemistry , chemistry , electrical engineering , gene , metallurgy , thermodynamics
In the field of a model predictive control of a permanent magnet synchronous motor (PMSM), the predictive flux control (PFC) has received great attention, which only takes the stator flux vector as the control variable instead of the electromagnetic torque and the stator flux amplitude. Because PFC does not involve the cumbersome setting of weight factors, it is a promising control algorithm. However, the prediction of the stator flux vector depends on motor parameters, which inevitably reduces the robustness of the control system. In order to solve this problem, this paper proposes a hybrid flux predictor‐based predictive flux control of PMSM drives. The proposed stator flux predictor combines the voltage prediction model and the current prediction model, and the proportional–integral regulator is utilised to control the switching between the two prediction models. Experimental results show that the proposed algorithm has better dynamic, steady‐state and robust performances than the traditional predictive flux control.