Grey‐prediction‐based double model predictive control strategy for the speed and current control of permanent magnet synchronous motor

2022 ◽  
Author(s):  
Hongguang Pan ◽  
Xinyi Huang ◽  
Penglin Guan ◽  
Shulin Liu
2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xuan Wu ◽  
Hui Wang ◽  
Xiaofang Yuan ◽  
Shoudao Huang ◽  
Derong Luo

In order to control the permanent-magnet synchronous motor system (PMSM) with different disturbances and nonlinearity, an improved current control algorithm for the PMSM systems using recursive model predictive control (RMPC) is developed in this paper. As the conventional MPC has to be computed online, its iterative computational procedure needs long computing time. To enhance computational speed, a recursive method based on recursive Levenberg-Marquardt algorithm (RLMA) and iterative learning control (ILC) is introduced to solve the learning issue in MPC. RMPC is able to significantly decrease the computation cost of traditional MPC in the PMSM system. The effectiveness of the proposed algorithm has been verified by simulation and experimental results.


2014 ◽  
Vol 700 ◽  
pp. 678-681
Author(s):  
Yu Lan Li ◽  
Tie Zhu Zhang ◽  
Hong Zhao ◽  
Ji Zhang

The paper gives a brief introduction of the permanent magnet synchronous motor (PMSM). The author gives the mathematical model under the simplified conditions and the PMSM rotor and stator impedance matrix. Besides, the author used AMESim to build a synchronous motor model on the basic of hysteresis current control strategy and set the parameters. A simulation was carried out and advantages and disadvantages of hysteresis current control strategy were analyzed.


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