## 1 Introduction  
In recent years, model predictive control has become a well-established control strategy, mainly due to its fast dynamic response, simplicity, and the ability to include constraints and nonlinearities in the controller design. Recently, predictive current and voltage control are the most popular case studies, where the predictions are carried out for each possible switching state to determine the proper actions. The decision is made through an optimization process evaluated by the cost function (CF) [1; 2; 3; 4; 5; 6; 7].  
The finite control set model predictive control (FCS-MPC) strategy provides a variable switching frequency due to the absence of the modulator. Therefore, noise and high voltage or current ripples are generated [8]. This noise leads to a spread spectrum, which decreases the overall performance of the system in terms of power quality [9; 10]. A large amount of research and investigations have been devoted to solving the variable switching frequency issue while maintaining the FCS-MPC characteristics and even improving them. Prior-art methods are aimed at embedding the modulator, and others intended to use the benefit of adding another objective in the CF to either control the switching frequency or make it fixed. For instance, the introduced method in [11] is based on including a suitable modulation scheme in the cost function minimization criterion of the predictive algorithm for a selected number of switching states. In [12], the authors proposed a new technique, periodic control based FCS-MPC, to solve the variable switching frequency issue, and uncharacteristic switching pattern without the need for a modulator.  
On the other hand, FCS-MPC can provide a better power quality if either the modulator or the periodic control based are not applied. The lack of the switching frequency regulation leaves an upper limit up to half of the sampling frequency, and that may lead to undesired losses in the semiconductors. Furthermore, the switching variations may be high or low based on the operation point and the system parameters.  
In this work, four model predictive algorithms will be assessed. In [13], a conventional FCS-MPC is proposed for grid forming converters in microgrids (MGs) applications. The proposed MPC is evaluating for a single objective, and no respect is given to the switching frequency regulation. In [14], an improvement of the traditional FCS-MPC presented in [13] has been proposed to provide better power quality. Both algorithms have been assessed up to 4 kW in terms of power quality and losses in [15]. Apparently, there is a lack of information on how both algorithms are classified comparing to the regulated MPC algorithms. Thus, the modulated predictive algorithms in [11; 12] will be analyzed and examined, in this work, with the algorithms in [13; 14].  
In order to perform the assessment, a three-phase voltage converter (VSC) has been used, as shown in Figure 1. The simulation study has been performed by developing a loss model using a PLECS circuit to make a preliminary investigation and obtain the losses distribution in each strategy [16; 17]. The purpose of this paper is not only to show how the selected MPC algorithms are influencing the converter efficiency, but also to highlight their preferences. Hence, in this paper, a comprehensive overview of the total harmonics distortion of the voltage (THDv) and efficiency using the discussed MPC techniques is presented. The rest of the article is organized as follows; the converter model is described in Section 2. In Section 3, the selected MPC algorithms are explained in detail. In Section 4, power loss calculations are presented. In Section 5, the obtained results and remarks are given. A proposal for standardized switching frequency is provided in Section 6. Finally, the summary of the work is given in Section 7.