Robust model based-predictive torque control of aviation AC induction motor

The dynamic, steady-state and robust performance of the drive motor are more demanding in aviation field. In recent years, Finite Control Set-Model Predictive Control (FCS-MPC) has become an international research frontier in the field of motor drive because of its fast dynamic response and good steady-state performance (at the same switching frequency). However, the prediction model depends on the motor parameters and has poor robustness. In particular, in FCS-MPC of the induction motor, the mismatched model causes the prediction error of electromagnetic torque, and then reduces the system performance and even leads to system instability. To solve this problem, a robust predictive torque control of induction motor based on the discrete hybrid prediction model is proposed. The traditional open-loop model for prediction of stator current is abandoned. An equation for prediction of stator current of the closed-loop model is established, and its stability and parameter design are studied. For prediction of stator flux vector, the traditional voltage model prediction method is abandoned, and a discrete hybrid prediction model integrating the voltage model and the current model is established. The proportional-integral regulator is used to adjust the smooth switching from the voltage model to the current model of the discrete hybrid prediction model. The electromagnetic torque is calculated by the current and the stator flux, which are predicted by the closed-loop model. The proposed algorithm is verified on a 2.2 kW induction motor experimental platform, and the experimental results show the effectiveness of the algorithm. © 2021, Beihang University Aerospace Knowledge Press. All right reserved.