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A novel type of Model Predictive Direct Torque Control (MP-DTC) is proposed in this paper. The future behavior of the plant is predicted using a discrete-time state-space model in the dq reference frame for a finite set of voltage vectors, which is pre-selected by a graph algorithm. The preferable input is chosen based on a cost function. Contrarily to conventional MP-DTC (and DTC), the stator flux is not explicitly controlled nor hysteresis bounds are used. The cost function is designed to meet multiple demands: torque reference tracking, Maximum Torque per Ampere (MTPA) tracking for high electrical efficiency, and limitation of the states to their maximum admissible values.
Preindl et al. (2013) studied this question.