Motor-Parameter-Free Model Predictive Current Control for PMSM Drives

Zhang, Xiaoguang; Zhang, Chenguang; Wang, Ziwei

Abstract

Conventional model predictive current control (MPCC) has superiorities on simple control structure, fast dynamic response time, and easy implementation. However, MPCC applied to permanent magnet synchronous motor has strong sensitivity to motor parameters, and incorrect model parameters will affect the control performance. Aiming to reduce the parameter sensitivity of MPCC, a motor-parameter-free MPCC (MPF-MPCC) method is proposed in this article, which is different from model-free predictive current control method where a look-up table or ultralocal model is used. In MPF-MPCC method, a current prediction model without any motor parameters is constructed and it only contains current difference and voltage difference. Besides, the effect of current difference and voltage difference on the current variation is analyzed. Then, a balance factor is designed to balance the effects of two components in the constructed current prediction model considering that the current difference and voltage difference have different dimensions. Finally, experiments demonstrate the effectiveness of the proposed method.

Más información

Título según WOS: Motor-Parameter-Free Model Predictive Current Control for PMSM Drives
Título de la Revista: IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volumen: 71
Número: 6
Editorial: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Fecha de publicación: 2024
Página de inicio: 5443
Página final: 5452
DOI:

10.1109/TIE.2023.3292874

Notas: ISI