A combined model predictive control/space vector modulation (MPC-SVM) strategy for direct torque and flux control of induction motors

Abstract

This work presents a new Direct Torque and Flux Control (DTFC) method for induction motors using a novel form of Model Predictive Control (MPC). This MPC strategy is novel from the point of view of the power supply (a three phase inverter) since, instead of using a single voltage vector as the control action during a complete sampling period of the controller, as is done in standard DTFC strategies, we propose to use an appropriately selected sequence of voltage vectors over the same period. The latter property allows us to synthesize smoother control actions, which considerably reduces the ripple component of the electromagnetic variables (current, flux, electromagnetic torque). The selection of the sequence of voltage vectors at each sampling time is carried out by the minimization of a quadratic cost function that penalizes the errors between flux magnitude and torque and their respective desired references over a prediction horizon. This is standard in MPC. However, in contrast to the usual form of MPC, we propose to apply the whole optimizing sequence (of duration equal to the sampling period) instead of only applying the first vector of the sequence in a receding-horizon fashion. Moreover, by an appropriate parameterization of the voltage vector sequence over the horizon we endow the proposed strategy with the same implementation strategy as used in the space vector modulation technique. This property achieves a fixed switching frequency for the voltage source inverter that feeds the motor. This is well-known to guarantee good performance of the inverter. Simulation results show that the proposed strategy considerably outperforms the standard MPC strategy at a very moderate computational cost increment.