Robust Deadbeat Finite-Set Predictive Torque and Flux Control for PMSM with Dynamic Model

Abstract

Deadbeat finite-set predictive torque and flux control has the advantages of fast dynamic response and reduced computational burden, but the system robustness is still a challenge in real-time implementation. This paper presents a novel deadbeat finite-set predictive torque and flux control strategy with a modified dynamical predictive model for permanent magnet synchronous motor (PMSM) drives to improve the robustness against mismatched parameters. By establishing sensitivity functions, the robustness of the system can be digitally quantified. The torque and flux predictive models with dynamic weighting factors are proposed to minimize phase current distortions and torque tracking errors caused by parameter variations. Finally, the simulation results verify the improved robustness of the proposed method.