Model-Free Predictive Current and Disturbance Rejection Control of Dual Three-Phase PMSM Drives Using Optimal Virtual Vector Modulation

Model-based predictive current control (MBPCC) relies heavily on adequate system modeling and accurate parameters. The detailed models of dual three-phase permanent magnet synchronous motors (PMSMs) contain mutual cross-coupling dynamics which make it difficult to extract accurate parameters. Also, some of the physical parameters of PMSMs are generally nonlinear functions of current and rotor position. In this article, a model-free predictive current control (MFPCC) based on an ultralocal model and an extended state observer is proposed for an asymmetrical dual three-phase (ADTP) PMSM. The MFPCC method is shown to provide superior current regulation when compared to the standard MBPCC approach under uncertain parameter conditions. Furthermore, the harmonic currents and the current ripple in the ADTP PMSM drive have been regulated to near-zero values by using optimized voltage vectors comprised of virtual vectors and null vectors. A generalized center-aligned pulsewidth modulation (PWM) scheme is presented to facilitate the synthesis of the optimal virtual voltage vectors for implementation on a low-cost digital signal processing platform. The performance improvements of the MFPCC with optimal virtual vector modulation are verified and compared with the conventional MBPCC method in both simulations and experiments on a surface-mount type dual three-phase PMSM.