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Recent advances in high-power applications employing voltage source converters have been primarily fuelled by the emergence of the modular multilevel converter (MMC) and its derivatives. Model predictive control (MPC) has emerged as an effective way of controlling these converters because of its high response. However, the practical implementation of MPC encounters hurdles, particularly in MMCs featuring many sub-modules per arm. This research introduces an approach termed folding model predictive control (FMPC), coupled with a pre-processing sorting algorithm, tailored for modular multilevel converters. The objective is to alleviate a significant part of the computational burden associated with the control of these converters. The FMPC framework combines multiple control objectives, encompassing AC current, DC current, circulating current, arm energy, and leg energy, within a unified cost function. Both simulation studies and real-time hardware-in-the-loop (HIL) testing are conducted to verify the efficacy of the proposed FMPC. The findings underscore the FMPC's ability to deliver fast response and robust performance under both steady-state and dynamic operating conditions. Moreover, the FMPC adeptly mitigates circulating currents, reduces total harmonic distortion (THD%), and upholds capacitor voltage stability within acceptable thresholds, even in the presence of harmonic distortions in the AC grid. The practical applicability of MMCs, notwithstanding the presence of a large number of sub-modules (SMs) per arm, is facilitated by the significant reduction in switching states and computational overhead achieved through the FMPC approach. [ABSTRACT FROM AUTHOR]

In some applications of microgrids and distributed generation, it is necessary to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an L C filter is usuallyconnected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltages and currents in these systems. However, these strategies have some drawbacks, particularly when multiple-input–multiple-output plants (MIMO) are controlled using single-input–single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross–coupling between different control loops and state variables. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an L C filter connected to a three-level neutral-point clamped converter. The strategy solves an optimisation problem to achieve control of the L C filter variables, i.e., currents and output voltages. Hardware-in-the-loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS–RT HIL platform and a dSPACE Microlab Box controller. In addition to the good dynamic performance of the proposed OSS–MPC, it is demonstrated using HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different operating conditions. [ABSTRACT FROM AUTHOR]

The Dual–Vector model predictive control (DV–MPC) method can improve the steady–state control performance of motor drives compared to using the single–vector method in one switching cycle. However, this performance enhancement generally increases the computational burden due to the exponential increase in the number of vector selections, lowering the system's dynamic response. Alternatively, limiting the vector combinations will sacrifice system steady–state performance. To address this issue, this paper proposes an enhanced DV–MPC method that can determine the optimal vector combinations along with their duration time within minimized calculation times. Compared to the existing DV–MPC methods, the proposed enhanced technique can achieve excellent steady–state performance while maintaining a low computational burden. These benefits have been demonstrated in the results from a 2.5k rpm permanent magnet synchronous motor drive. [ABSTRACT FROM AUTHOR]

In this paper, a modification is proposed in the conventional finite control set model predictive controller (FCS-MPC) applied in the three-phase voltage source inverter's (VSI's) output current control with resistive-inductive (RL) load. It comprises the introduction of the novel type of hysteresis-based comparator in the cost function evaluation implemented with a single-step prediction horizon, which represents an improvement when compared to existing solutions. In this way, effective reduction of the VSI output voltage high switching frequency is achieved, by implementing a simplified predictive current control algorithm. Also, an effective disturbance estimator algorithm is proposed, which enables the operation of a hysteresis FCS-MPC with RL load and with unmeasurable external disturbances. Simulation and experimental tests are used in the paper to prove the effectiveness of the proposed solution, showing the extent of the impact that the chosen cost evaluation comparator hysteresis value has on the resulting average power converter switching frequency, for the model predictive control current controller operating with the zero steady-state error. [ABSTRACT FROM AUTHOR]

Microgrids represent a promising energy technology, because of the inclusion in them of clean and smart energy technologies. They also represent research challenges, including controllability, stability, and implementation. This article presents a dSPACE-control-platform-based implementation of a fixed-switching-frequency modulated model predictive control (M 2 PC) strategy, as an inner controller of a two-level, three-phase voltage source inverter (VSI) working in an islanded AC microgrid. The developed controller is hierarchical, as it includes a primary controller to share the load equally with the other power converter with its own local modulated predictive-based controller. All details of the implementation are given for establishing the dSPACE-based implementation of the control on a dSPACE ds1103 control platform, using MATLAB/Simulink for the controller design, I/O implementation and configuration with the embedded dSPACE's real-time interface in Simulink, and then using the ControlDesk software for monitoring and testing of the real plant. The latter consists of the VSI operating with  L C L  filters, and sharing an  R L  load with a paralleled VSI with exactly the same controller. Finally, the obtained experimental waveforms are shown, with our respective conclusions representing this work, which is a very valuable tool for helping microgrid researchers implement dSPACE-based real-time simulations. [ABSTRACT FROM AUTHOR]

This paper compares two finite-control-set model predictive control (FCS-MPC) strategies in the context of a grid-connected single-phase quasi-Z source inverter (SP-qZSI). Both schemes use discrete-time models of the inductor current and capacitor voltage for the DC side, as well as the output current on the AC side. To enhance the converter's performance, given the non-minimum phase characteristics of the DC side, a long prediction horizon is implemented for the predictive control. However, a horizon of this nature can be highly demanding in terms of processing load, rendering it inapplicable for some microcontrollers. To address this issue and mitigate the processing load, an alternative control strategy is presented that divides the total number of candidate solutions to be evaluated into smaller segments. The performance of the two control strategies is compared using total harmonic distortion (THD) and simulation times as evaluation metrics. The results indicate that the proposed strategy achieves significantly shorter simulation times than the compared control strategy when increasing the prediction horizon. Additionally, a reduction in the THD was observed in the proposed strategy, reaching an average of 2.8%, which is lower than the compared strategy that exhibited THD close to 3.5%. [ABSTRACT FROM AUTHOR]

Finite Set Model Predictive Control (FS-MPC) is a widely used technique in power electronic converter applications. One challenge in FS-MPC implementation is selecting appropriate weighting factors, as there is currently no established methodology for finding the best values. An alternative approach is to consider cost functions without weighting factors, as used by the Sequential Model Predictive Control (SMPC). In this paper, the performance of SMPC applied to induction motors is analyzed. The SMPC strategy involves sequentially evaluating simple cost functions by considering a limited number of available switching states for the power electronic converter. This number is the control parameter of the SMPC. The parameter's domains and a selection criteria based on THD were established in this investigation. The power converter topologies studied include the Voltage Source Inverter (VSI) and the Neutral Point Clamped three-level (3L-NPC). Simulations performed in PLECS software and Hardware-in-the-Loop (HIL) tests using an RT Box for valid parameters satisfy the characteristics of the classical predictive control, such as good control variables tracking and high dynamic response. For a VSI converter, increasing the control parameter results in reduced harmonic distortion, while for an NPC converter, optimal results are achieved with control parameter values within a specific range. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-switching-frequency modulated model predictive control (M 2 PC) is established for a two-level three-phase voltage source inverter (VSI) working in an islanded AC microgrid. These small-scale power systems are composed by two or more VSIs which interface DGs, controlling the voltage amplitude and frequency in the system, and simultaneously sharing the load active and reactive power. Generally, these operational characteristics are achieved using hierarchical linear control loops, but with challenging limitations such as slow transient reaction to disturbances and high proneness to be affected by parameter modifications. Model predictive control may solve these issues. Nevertheless, the most used and developed predictive control scheme, the finite-set model predictive control (FS-MPC), presents the drawback of having the harmonic spectrum spread over all the frequencies. This brings issues with coupling between the different hierarchical control levels of the whole microgrid system, and eventually, when designing the filters for main-grid connection. This paper aims to solve these issues by developing the fixed-switching-frequency M 2 PC working with higher-level control loops for operation in an islanded AC microgrid. These advantages are proved in an AC microgrid configuration where methodology for paralleling multiple M 2 PC-regulated VSIs is described, with rapid transient response, inherent stability, and fully decentralised operation of individual VSIs, achieving proper load power sharing, eliminating circular currents, and proper waveforms for output currents and capacitor voltages. All these achievements have been confirmed via simulation and experimental verification. [ABSTRACT FROM AUTHOR]

Modulated model predictive current control techniques are considered an interesting option to control multiphase drives due to their control flexibility and fast dynamic response. However, a practical stability study of those techniques is still missing. This article presents an experimental stability study, to quantify the limits of stability, to modulated predictive current controllers applied to an asymmetrical six-phase induction machine. Experimental results are presented to verify the theoretical analysis results in terms of stability ranges regarding sampling frequency and rotor speed. [ABSTRACT FROM AUTHOR]

Model-based predictive control techniques, with finite set control, are considered an interesting option to control multiphase drives due to their control flexibility and fast dynamic response. However, those techniques have some drawbacks such as a high computational cost, poor (x-y) currents reduction, and steady-state error, especially at high speeds. To improve some of these drawbacks, modulation stages have been presented as an alternative. However, some of those drawbacks have not been improved. This article proposes a novel approach to the classic predictive current control (PCC) applied to an asymmetrical six-phase induction machine, where a space vector modulation with specific vectors is used in order to improve the (x-y) currents, the steady-state error and total harmonic distortion (THD) at high operation speeds. Experimental results are presented to demonstrate the characteristics of the proposed control technique in terms of current tracking, (x-y) currents reduction and THD of stator currents compared to the classic PCC. [ABSTRACT FROM AUTHOR]

Matrix converters are a well-known class of direct AC--AC power converter topologies that can be used in applications, where compact volume and low weight are necessary. For good performance, special attention should be paid to the control scheme used for these converters. The model predictive control strategy is a promising, straightforward and flexible choice for controlling various different matrix converter topologies. This work provides a comprehensive study and detailed classification of several predictive control methods and techniques, discussing special capabilities they each add to the operation and control scheme for different matrix converter topologies. This study also considers the issues regarding the implementation of model predictive control strategies for matrix converters. This survey and comparison are intended to be a useful guide for solving the related drawbacks of each topology and to enable the application of this control scheme for matrix converters in practical applications. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) has emerged as a real alternative for the control of different topologies of power converters. In particular, MPC has been successfully applied in matrix converters, significantly reducing the difficulty of control compared with classical techniques. In this study, a predictive voltage control strategy for a four-leg indirect matrix converter is proposed. The idea is based on the discrete minimisation of a cost function in order to select the best vector state of the power converter to be applied in the next sampling instant. Experimental results are presented to validate the proposal under several operating points. [ABSTRACT FROM AUTHOR]

This study proposes a robust and powerful finite control set-model predictive control (MPC) algorithm to control the load current with lower total harmonic distortion and efficient reference tracking. In this control, the cost functions are determined for all the possible switching states of the converter and a switching state is selected corresponding to the minimum cost function for actuating the converter in the next sampling time period. To justify the performance of the proposed MPC scheme, a comprehensive study with the carrier-based pulse-width modulation, hysteresis current control and proposed minimum cost function-based MPC of the three-phase load current has been verified in MATLAB Simulink as well as the validation with dSPACE RTI1104 experimentation. This study validates the robustness of the proposed minimum cost function-based MPC control with a RL-load and three-phase induction motor (IM) load. The simulation and experimental results justifies the proposed MPC algorithm with potential tracking of the RL-load current corresponding to the reference current with lower harmonic contents as well as tracking of predictive torque and flux compared to the nominal torque and reference flux of IM, respectively. [ABSTRACT FROM AUTHOR]

This paper describes the experimental implementation of the model predictive current control algorithm for a two-level four-leg inverter operating under balanced, unbalanced, and nonlinear loading conditions. The proposed scheme is designed to predict the future behavior of the load currents for each of the 16 possible switching states of the converter. The control method chooses a switching state that minimizes the error between the output currents and their references. The algorithm is embedded using a MATLAB/Simulink software environment, and experimental results based on the dSPACE DS\1103 controller are provided. These results verify the advantages of the proposed control strategy in terms of robustness under filter and load parameter variations, average neutral-leg switching frequency reduction, reference tracking error, and percentage total harmonic distortion. [ABSTRACT FROM PUBLISHER]

In this paper, a simple model predictive current control strategy is proposed for four-leg inverters to deliver power to the (un)balanced/(non)linear loads. Unlike classical control schemes, the proposed method does not require current PI controllers or a complex modulation stage. The discrete-time model of the inverter, filter, and load are used to predict the future behavior of the load currents for each of the 16 possible switching states. The control method chooses a switching state that minimizes the error between the output currents and their references. The performance of the proposed method has been investigated for perturbations in the filter and load parameters. The neutral-leg switching frequency reduction algorithm is also proposed to improve the efficiency of the converter. The feasibility of the proposed method is verified in this first part, through simulation results. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

The operation of single-phase Modular Multilevel Converter (MMC) is analyzed in the paper. A mathematical model of the converter is developed and described, based on which the structure and selection of parameters for Classical Control and Optimal Switching State Model Predictive Control (OSS-MPC) are defined. Additionally, the procedure for the determination of circuit parameters, such as submodule capacitance and arm inductance, is described and carried out. The listed control methods are designed and evaluated in Virtual Hardware-in-the-Loop together with single-phase MMC power circuit, regarding three control objectives: AC current control, voltage balancing control and circulating current control. Control methods are evaluated for both steady-state and transient performance and compared based on nine criteria: AC current reference tracking, THD of AC current and voltage, submodule capacitor voltage balancing, total submodule voltage control, circulating current magnitude and THD, number of control parameters and computational complexity. This is the first time that a fair comparison between Classical Control and MPC is considered in literature, resulting in superior performance of both control methods regarding four different criteria and the same performance regarding AC current reference tracking. [ABSTRACT FROM AUTHOR]

The single-phase matrix converter is an AC-AC power topology which consists of six bidirectional switches and it is considered the key unit in cascade or multilevel configurations. In this paper, a comparison between two control techniques is presented, one based on a proportional-integral-derivative control module with a pulse width modulator, and the other known as finite-state model predictive control. Simulation and experimental results are presented and discussed to demonstrate the feasibility and performance of both techniques. [ABSTRACT FROM AUTHOR]

In applications such as multiphase motor drives, classical predictive control strategies are characterized by a variable switching frequency which adds high harmonic content and ripple in the stator currents. This paper proposes a model predictive current control adding a modulation stage based on a switching pattern with the aim of generating a fixed switching frequency. Hence, the proposed controller takes into account the prediction of the two adjacent active vectors and null vector in the (α - β) frame defined by space vector modulation in order to reduce the (x-y) currents according to a defined cost function at each sampling period. Both simulation and experimental tests for a six-phase induction motor drive are provided and compared to the classical predictive control to validate the feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]