Single‐loop model prediction control of PMSM with moment of inertia identification.

In order to improve the dynamic response performance and robustness of the permanent magnet synchronous motor control system and optimize the parameter adjustment of the control system, a motor control method based on single‐loop model prediction and moment of inertia parameter identification with forgetting factor is proposed. First, the motor state equation in the prediction model is designed, and the single‐loop model predictive control method is proposed. Then, comparing the effects of various parameters of the motor on the running stability of the motor, a least‐squares identification method based on forgetting factor is added to identify the moment of inertia online and optimize the prediction model in real time. The simulation and experimental results show that the proposed method has good dynamic performance for the permanent magnet synchronous motor adapting to the rotational speed and load variation. At the same time, the addition of the moment of inertia identification enhances the accuracy and system robustness of the motor model parameters during the model prediction process. This method provides an effective way of engineering control. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]