Simplified finite control set model predictive control for induction motor drive without weighting factors

Abstract

Predictive torque control (PTC) is a kind of finite control set model predictive control (FCSMPC) technique and this method is one of the widely used modern control techniques for induction motor drives. This control method becomes popular due to its simple structure, fast dynamic response and ability to include additional constraints (control parameters) into the objective function of the control algorithm. However, weighting factors are used to maintain the relative importance of different control parameters in the objective function. The primary concern of implementing PTC is the selection suitable weighting factors in the objective function. In this paper, tuning of weighting factor is eliminated by selecting stator flux as the only control parameter in the objective function. Further, a predefined switching table based on stator flux location and torque error is used for the predictions of the control parameter. Hence, computational burden significantly reduces in proposed method compared to conventional PTC. The simulation results are presented for a 2-level voltage source inverter (VSI) fed 2.2 kW induction motor by using MATLAB/Simulink. These results are compared with conventional PTC and the merits of the proposed control algorithm are highlighted under various operation conditions.