Model-Based Predictive Direct Control Strategies for Electrical Drives: An Experimental Evaluation of PTC and PCC Methods

Abstract

Model-based predictive direct control methods are advanced control strategies in the field of power electronics. To control an induction machine (IM), the predictive torque control (PTC) method evaluates the electromagnetic torque and stator flux in the cost function. The switching vector selected for the use in the insulated gate bipolar transistors (IGBTs) minimizes the error between references and the predicted values. The system constraints can be easily included. The predictive current control (PCC) strategy assesses the stator current in the cost function. The weighting factor is not necessary. Both the PTC and PCC methods are very useful direct control methods that do not require the use of a modulator. In this paper, the PTC and PCC methods are carried out experimentally for an IM on the same test bench. The behaviors and the robustness in steady state and the performances in transient state are evaluated.