Robustness Enhanced Predictive Control for Dual Three Phase PMSM with Duty Ratio Modulation and Parameter-Free Solution

Abstract

The classical model predictive control not only relies on the motor model but also is sensitive to the system parameters. To improve the robustness of the model predictive control system, this article proposes a parameter-free predictive control for a dual three-phase PMSM with duty ratio modulation. First, the free-model theory is employed to reconstruct the prediction model of the motor, of which no parameters are needed. So, the problem of parameter mismatch between the motor and the inverter can be handled, and enhance the robustness of the system as well. Moreover, the ultra-local model is optimized with the forgetting factor recursive least-squares algorithm to improve the identification accuracy of the estimated value. Finally, the deadbeat duty ratio modulation solution is introduced to further improve operational performance while ensuring the robustness of the system. Simulation and experiment verify the feasibility and effectiveness of the proposed algorithm.