Modulated Model Predictive Control for Induction Motor Drives with Sequential Cost Function Evaluation

Sequential model predictive control is a recent innovation in the high-performance control of electric drives. The elimination of weighting factors and associated tuning work is among the biggest advantages of this MPC implementation. The cost function evaluation takes place in two steps with each step narrowing down the choice of optimal voltage vector to be applied at the next switching instant. Like the conventional finite control states MPC, the sequential MPC also has a disadvantage of variable switching frequency. In this paper, this problem is addressed by considering the sequential MPC implementation with a modulator. After two-step cost function evaluation, the optimal and second optimal voltage vectors’ duty cycles are computed based on the slope of the controlled variables. This preserves the optimality of the solution while, at the same time, guaranteeing constant switching frequency and reduced current and torque ripples in the drive response.