Augmented Continuous-Control-Set Model Predictive Current Control for Dual Three-Phase PMSM Drives
Zonghao Su, Xiaodong Sun, Gang Lei, Ming Yao, Lei Zhang
Abstract
This article introduces an augmented continuous-control-set model predictive current control (ACCS-MPCC) for dual three-phase permanent magnet synchronous machines (DTP-PMSMs) to achieve comprehensive 4-D predictive current control. First, an optimization problem is formulated based on a cost function incorporating parameter disturbances and digital delays as disturbance terms to enhance the drive system's robustness. The complete voltage plane, regular switching characteristics, and improved cycle-by-cycle tracking control contribute to superior steady-state and transient performance, alongside excellent harmonic suppression capabilities within the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x–y</i> plane. Second, a moving horizon estimator (MHE) is employed to estimate the disturbance term, with its stability being mathematically substantiated. The utilization of MHE resolves the dependence of control performance on parameter accuracy, as commonly encountered in model predictive control, and effectively addresses the issue of digital delay. Finally, this article thoroughly investigates the parameter sensitivity of the continuous-control-set model predictive current control via experimental analysis of a DTP-PMSM system. The effectiveness of the proposed method is affirmed through comparative analysis, which demonstrates that the proposed ACCS-MPCC significantly mitigates the nonoptimal susceptibility issues inherent in multiphase motor systems.