Parameter Robust Predictive Current Control for PMSM Drives Based on Self-Tuning Incremental Model and Voltage Constraint Compensation

Abstract

Aiming to enhance the robustness and transient performance under model parameter mismatch, this article proposes a self-tuning incremental model-based predictive current control (STIM-PCC) strategy for permanent-magnet synchronous motor drives. In conventional incremental predictive current control scheme, although parameters such as permanent magnetic flux linkage and stator resistance are not required, stator inductance is still necessary for the predictive model. When the stator inductance mismatch occurs, prediction error is inevitable, leading to weakened robustness and deteriorated performance. To solve this issue, a novel STIM-PCC strategy is proposed, where the prediction error that indicates the inductance mismatch is adopted to tune the nominal inductance. In this way, the incremental model is updated adaptively and the precise predictive control can be achieved. Moreover, to enhance the tuning accuracy in the overmodulation region, a voltage constraint compensation method is put forward, which can effectively reduce the current drop during dynamic process. Compared to conventional scheme, the parameter robustness is significantly strengthened, where the inductance mismatch can be detected and corrected in time. Besides, not only the current fluctuation is reduced, but the settling time is shortened, thus greatly improving the transient performance. Experiments are carried out to validate the effectiveness of the proposed scheme.