Research on Grey Predictive Control of PMSM Based on Reduced-order Luenberger Observer

• DOI: 10.1007/s42835-021-00797-3
• Publication Date: 2021-06-28T11:03:36Z
• Authors: Xianghui Huang; Penglin Guan; Hongguang Pan; Shulin Liu; Guanghui Du; Xinyi Huang; Xueyan Wang
• Keywords: Model Predictive Control; Observer (physics)

To further improve the dynamic and anti-interference performance of permanent magnet synchronous motor (PMSM) control system, a dual closed loop model predictive control (MPC) strategy combining with grey prediction and reduced-order Luenberger observer is proposed in this paper for speed and current control. To be specific, firstly, the dual closed loop MPC strategy is introduced based on the mathematical model of PMSM, that is, the model predictive controller is used for the outer loop of speed, and the deadbeat predictive controller for the inner loop of current. Secondly, considering the grey prediction method can establish grey model and whiten the system grey quantity to some extent, it is used in the PMSM control system to improve the dynamic performance. Finally, to solve the problem that the motor is easy to be affected by disturbances, a reduced-order Luenberger observer is designed to combine with the model predictive controller to improve the system anti-interference performance. The simulation results show that the dual MPC strategy based on grey prediction makes the system more stable and dynamic response faster, while the dual MPC strategy combining with the grey prediction and the reduced-order Luenberger observer makes the system more resistant to load disturbance.