Model predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the latest developments in MPC for power converters and drives, describing the current state of this control strategy and analyzing the new trends and challenges it presents when applied to power electronic systems. The paper revisits the operating principle of MPC and identifies three key elements in the MPC strategies, namely the prediction model, the cost function, and the optimization algorithm. This paper summarizes the most recent research concerning these elements, providing details about the different solutions proposed by the academic and industrial communities.

Energy storage systems (ESSs) are enabling technologies for well-established and new applications such as power peak shaving, electric vehicles, integration of renewable energies, etc. This paper presents a review of ESSs for transport and grid applications, covering several aspects as the storage technology, the main applications, and the power converters used to operate some of the energy storage technologies. Special attention is given to the different applications, providing a deep description of the system and addressing the most suitable storage technology. The main objective of this paper is to introduce the subject and to give an updated reference to nonspecialist, academic, and engineers in the field of power electronics.

Model-based predictive control (MPC) for power converters and drives is a control technique that has gained attention in the research community. The main reason for this is that although MPC presents high computational burden, it can easily handle multivariable case and system constraints and nonlinearities in a very intuitive way. Taking advantage of that, MPC has been successfully used for different applications such as an active front end (AFE), power converters connected to resistor inductor RL loads, uninterruptible power supplies, and high-performance drives for induction machines, among others. This article provides a review of the application of MPC in the power electronics area.

The use of an inverter with an output LC filter allows for generation of output sinusoidal voltages with low harmonic distortion, suitable for uninterruptible power supply systems. However, the controller design becomes more difficult. This paper presents a new and simple control scheme using predictive control for a two-level converter. The controller uses the model of the system to predict, on each sampling interval, the behavior of the output voltage for each possible switching state. Then, a cost function is used as a criterion for selecting the switching state that will be applied during the next sampling interval. In addition, an observer is used for load-current estimation, enhancing the behavior of the proposed controller without increasing the number of current sensors. Experimental results under linear and nonlinear load conditions, with a 5.5-kW prototype, are presented, verifying the feasibility and good performance of the proposed control scheme.

Model predictive control with a finite control set has emerged as a promising control tool for power converters and drives. One of the major advantages is the possibility to control several system variables with a single control law, by including them with appropriate weighting factors. However, at the present state of the art, these coefficients are determined empirically. There is no analytical or numerical method proposed yet to obtain an optimal solution. In addition, the empirical method is not always straightforward, and no procedures have been reported. This paper presents a first approach to a set of guidelines that reduce the uncertainty of this process. First a classification of different types of cost functions and weighting factors is presented. Then the different steps of the empirical process are explained. Finally, results for several power converters and drives applications are analyzed, which show the effectiveness of the proposed guidelines to reach appropriate weighting factors and control performance.

This paper proposes an extended state observer (ESO) based second-order sliding-mode (SOSM) control for three-phase two-level grid-connected power converters. The proposed control technique forces the input currents to track the desired values, which can indirectly regulate the output voltage while achieving a user-defined power factor. The presented approach has two control loops. A current control loop based on an SOSM and a dc-link voltage regulation loop which consists of an ESO plus SOSM. In this work, the load connected to the dc-link capacitor is considered as an external disturbance. An ESO is used to asymptotically reject this external disturbance. Therefore, its design is considered in the control law derivation to achieve a high performance. Theoretical analysis is given to show the closed-loop behavior of the proposed controller and experimental results are presented to validate the control algorithm under a real power converter prototype.