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Abstract--Based on the internal model principle, repetitive controller (RC) is capable to reduce periodic torque ripple by generating a compensating action that consequently need to be synchronized with the original ripple. However, the synchronization is difficult to achieve using the conventional RC when the sampling frequency is not integer multiple of the speed (known as fractional delay issue), or when the speed varies widely. To solve this problem, this paper presents a fractional delay variable frequency torque ripple reduction method for PMSM drives using the combination of anglebased RC and deadbeat current control (DBCC). Four aspects of innovations are included in the proposed control to improve the synchronization. The experimental results show that the proposed control can effectively reduce torque ripple even during speed and load transient.

-This paper investigates the feasibility of a sensorless field oriented control (FOC) combined with a finite control set model predictive current control (FCS-MPC) for an interior permanent magnet synchronous motor (IPMSM). The use of a FCS-MPC makes the implementation of most of the existing sensorless techniques difficult due to the lack of a modulator. The proposed sensorless algorithm exploits the saliency of the motor and the intrinsic higher current ripple of the FCS-MPC to extract position and speed information using a model-based approach. This method does not require the injection of additional voltage vectors or the periodic interruption of the control algorithm and consequently it has no impact on the performance of the current control. The proposed algorithm has been tested in simulation and validated on an experimental setup, showing promising results.

Abstract-In recent years Model Predictive Control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. MPC offers many advantages over more traditional control techniques such as the ability to avoid cascaded control loops, easy inclusion of constraint and fast transient response. On the other hand, the controller computational burden increases exponentially with the system complexity and may result in an unfeasible realization on modern digital control boards. This paper proposes a novel Distributed Model Predictive Control, which is able to achieve the same performance of the classical Model Predictive Control whilst reducing the computational requirements of its implementation. The proposed control approach is tested on a AC/AC converter in a back-to-back configuration used for power flow management. Simulation results are provided and validated through experimental testing in several operating conditions. Index Terms-Predictive control, Nonlinear control systems, Back-to-back converters.