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.

New regulations impose more stringent limits on current harmonics injected by power converters that are achieved with pulsewidth-modulated (PWM) rectifiers. In addition, several applications demand the capability of power regeneration to the power supply. This work presents the state of the art in the field of regenerative rectifiers with reduced input harmonics and improved power factor. Regenerative rectifiers are able to deliver energy back from the dc side to the ac power supply. Topologies for single- and three-phase power supplies are considered with their corresponding control strategies. Special attention is given to the application of voltage- and current-source PWM rectifiers in different processes with a power range from a few kilowatts up to several megawatts. This paper shows that PWM regenerative rectifiers are a highly developed and mature technology with a wide industrial acceptance.

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.

This paper investigates the use of a virtual synchronous machine (VSM) to support dynamic frequency control in a diesel-hybrid autonomous power system. The proposed VSM entails controlling the grid-interface converter of an energy storage system (ESS) to emulate the inertial response and the damping power of a synchronous generator. In addition, self-tuning algorithms are used to continuously search for optimal parameters during the operation of the VSM in order to minimize the amplitude and rate of change of the frequency variations and the power flow through the ESS. The performances of the proposed self-tuning (ST)-VSM and the constant parameters (CP)-VSM were evaluated by comparing their inertial responses and their damping powers for different scenarios of load variations. For the simulated cases, the ST-VSM achieved a similar performance to that of the CP-VSM, while reducing the power flow through the ESS in up to 58%. Moreover, in all the simulated scenarios, the ST-VSM was found to be more efficient than the CP-VSM in attenuating frequency variations, i.e., it used less energy per Hertz reduced.

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.