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In this paper, two kinds of observer-based sensorless predictive torque control methods are proposed. The predictive method is based on examining feasible voltage vectors (VVs) in a prescribed cost function. The VV that minimizes the cost function is selected. A novel robust prediction model is presented. The prediction model includes sliding mode feedbacks. The feedback gains are assigned by the H-inf method. Two kinds of observers are applied for flux and speed estimation, i.e., sliding mode full order observer and reduced order observer. In order to verify the proposed method, simulation and experimental results are presented in wide speed range. A comparison of the two methods is performed based on the results. [ABSTRACT FROM AUTHOR]

In this paper, an improved finite control set-model predictive control (FCS-MPC) with an optimized weighting factor is presented. The main goal of this paper is reducing the torque ripples when the FCS-MPC is implemented by means of the two-level inverter. For this purpose, the weighting factor is calculated via an optimization method. The optimization is based on dividing the control interval into two parts: active time for applying the active voltage vectors and zero time for applying the zero voltage. With this technique, the torque ripple is calculated as a function of weighting factor and it is optimized. The method is validated by simulations and experiments, using two-level inverter, at two speed regions (nominal speed and low speed). The results are compared with conventional FCS-MPC. [ABSTRACT FROM AUTHOR]