The paper deals with a newly developed sequential model predictive control strategy for the highperformance control of electric drives. The sequential nature of cost function evaluation allows to eliminate weighting factors whose tuning is not straightforward. In the first cost function evaluation, torque (or flux) error is minimized and, the second evaluation minimizes the flux (or torque) error. The first optimization generates two optimal voltage vectors that give minimum error for the controlled variable and the second optimization tests only the selected two vectors to find the global optimal. In this paper, a detailed analysis of the sequential MPC is carried out with a focus on the inversion of sequence of optimization with respect to the original algorithm. The paper also analyses the effect of selecting more than two vectors from the first evaluation and explains to the reader why some numbers of selected vectors produce flux and torque distortions while others do not control flux and torque at all

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.Index Terms-Model predictive control, variable speed drives, predictive torque control.