Sequential MPC Strategy for High Performance Induction Motor Drives: a detailed analysis

The paper deals with a newly developed sequential model predictive control strategy for the high-performance 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