Abstract: The control performance of model predictive control (MPC) depends on the accuracy of the model. This paper proposes a robust continuous control set model predictive control (CCS-MPC) scheme for permanent magnet synchronous motors (PMSMs). This scheme adopts a two-step optimization scheme. The first step solves the unconstrained convex quadratic programming problem, and the second step uses the cost function to solve the voltage and current constraints to obtain the optimal output reference voltage, which reduces the computational burden. In addition, after using an incremental prediction model to eliminate the impact of permanent magnet magnetic flux, an inductance recognition scheme is designed to extract accurate inductance values. Finally, experiments demonstrate the effectiveness of this method in improving robustness.
 

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