This paper addresses to some of the latest contributions on the application of Finite Control Set Model Predictive Control (FCS-MPC) in Power Electronics. In FCS-MPC , the switching states are directly applied to the power converter, without the need of an additional modulation stage. The paper shows how the use of FCS-MPC provides a simple and efficient computational realization for different control objectives in Power Electronics. Some applications of this technology in drives, active filters, power conditioning, distributed generation and renewable energy are covered. Finally, attention is paid to the discussion of new trends in this technology and to the identification of open questions and future research topics.

This paper presents a comparative study between field-oriented control (FOC) and Predictive Torque Control (PTC) applied to induction machines. Both strategies are implemented on the same experimental bench and similar tests are performed. Furthermore, they were previously adjusted to get an equivalent switching frequency at a specific operation point, achieving the fairest possible comparison at steady state. Experimental results verify that PTC can achieve results similar to FOC, possibly even improving performance in transient conditions.

Finite control set model predictive control is an emerging alternative in the control of power converters and drives. The method allows flexible control schemes with fast dynamics. However, the standard formulation of this type of controllers is based on a minimization of a single cost function. This optimization method requires weighting factors that depend on the system parameters and operating point. The calculation of these factors is achieved through a nontrivial process. In this paper, a predictive torque and flux control of an induction machine drive fed by a three-phase two-level voltage source inverter is developed. The proposed strategy replaces the single cost function with a multiobjective optimization based on a ranking approach. This approach makes the tuning of weighting factors unnecessary for a correct operation. Simulation and experimental results on steady state and dynamic operation are presented to illustrate the good behavior of the drive.

Finite-states model predictive control is a rising alternative in the control of power converters and drives. Successful application to different topologies and applications such as two-level voltage source inverters, neutral-point-clamped and cascaded H-bridge inverters, and matrix converters has shown its potential in power converters. However, when multiple control objectives are desired, weighting factors are required to appropriately select the switching states. The selection of these factors is a time-consuming and complex task. In this work, the standard selection stage is replaced by a fuzzy decision-making strategy, considering, as a case study, the control of both load and supply currents in the direct matrix converter (DMC). As a result, weighting-factor selection is avoided, and a simple selection scheme is obtained for this application. In addition, a more natural design approach to the state selection is opened for other applications. Simulation and experimental results are presented to validate the approach in an experimental DMC prototype.

This paper presents a control method for direct matrix converters that combines the advantages of predictive control with active damping. The active damping is used to suppress the resonance of the input filter. A discrete-time model of the converter, the input filter, and the load parameters are used to predict the behavior of the input reactive power on the supply side and the output currents for each valid switching state. The control method selects the best commutation state, according to an optimizing algorithm and a cost function, in order to generate unity input displacement power factor with high-quality waveforms. The active damping method is based on a virtual harmonic resistor that damps the filter resonance. This paper shows simulated and experimental results to demonstrate that the proposed control method can generate good tracking of the output current references, achieve unity input displacement power factor, and reduce the input current distortion caused by the input filter resonance.

Matrix converters (MCs) are a very attractive alternative to conventional back-to-back converters with dc links. In this paper, a performance comparison between the well-established space vector modulation (SVM) technique and model predictive control (MPC) is presented for the current regulation in a direct MC. Both methods are analyzed and contrasted through simulation and experimental results. In order to establish their strengths and weaknesses, the assessment is made by measuring and comparing output and input currents and voltages with the same voltage source and load current conditions. Our results show that MPC is simpler than SVM from a conceptual point of view and provides better source current behavior, particularly with a distorted source voltage.