The three-phase grid-connected inverters are widely employed in various distributed generation (DG) applications. The use of LCL filters at their outputs has proven several benefits, regarding passive component size reduction and improved high-frequency harmonics elimination. However, the resonance of the LCL filter hinders their application. Another issue with applying model predictive control (MPC) in LCL-filter-based DGs, as a high-performance controller, is the difficulty in including the various control objectives in a single cost function. The main issues include the necessity to compensate for various delays in the control loops and the selection of a proper weighting factor between objectives. Therefore, this paper proposes an efficient MPC method for grid-connected LCL-filtered DG inverters. The proposed MPC employs proper delay compensation for current/voltage loops. Furthermore, the proposed method incorporates various controlled variables in a single-objective function, eliminating the need for cascaded control loops. The proposed MPC is simulated in MATLAB/Simulink, and different test cases of active/reactive power demands are provided. The obtained results show the robust resonance-free performance of the proposed MPC method.

This paper presents a Continuous Control Set Model Predictive Control (CCS-MPC) enhanced with Nestorov Accelerated Gradient (NAG) for real-time closed-loop control of Cascaded H-Bridge (CHB) converters under normal operation and with faults on the power cells. The proposed method addresses limitations of conventional Finite Control Set MPC (FCS-MPC), including variable switching frequency and the computational burden for the control of multilevel converters. The main contributions of the proposed CCS-MPC with NAG are: (i) derivation of a dynamic model that enables simultaneous control of line currents and common-mode voltages under normal and fault conditions; (ii) formulation of the CCS-MPC problem as a convex, box-constrained optimization, enabling the use of an efficient projection-based solution within each NAG iteration to enforce feasibility; (iii) offline computation of matrices to minimize online computational burden; and (iv) a closed-loop reference voltage control to ensure fault-tolerant operation. The effectiveness of the proposed CCS-MPC with NAG is validated through real-time Hardware-in-the-Loop (HIL) simulations, that confirm the fast dynamic response and robust performance of the proposed algorithm under fault conditions and demonstrate its suitability for high-performance and reliable operation for industrial drives and grid-connected applications.

This paper presents a hybrid controller based on fractional order control (FOC) with finite control set model predictive control (FCS-MPC) for LCL grid-tied single-phase multilevel inverters. Recently, FCS-MPC has received major interest in fast control tracking and handling several control objectives together in a single cost function. However, in the case of LCL grid-tied inverters, the control of the inverter side current, grid side current, and AC filter capacitor voltage, in addition to the voltage balance of dc-link capacitors, makes the design process of a single cost function more difficult to reach. Therefore, a cascaded FOC resonant controller for grid-side current with inner FCS-MPC for controlling inverter-side current and capacitor voltages is proposed for a single-phase five-level H-bridge T-type grid-tied inverter. The proposed controller merges the characteristics of FOC, FCS-MPC, and resonant controllers, improving system performance. Simulation results are provided to verify the superior tracking and control performance of the new proposed controller.

This article presents an optimization in implementing a DTC control scheme using a 3L-NPC inverter to control the speed of a three-phase induction machine. Regarding the DTC strategy, 3 and 5-level hysteresis controllers were used to control the stator flux and electromagnetic torque, respectively. The traditional implementation of the scheme [2], shows good results regarding the motor speed response; however, the electromagnetic torque developed by the motor presents various issues: significant ripples in torque produced by a poor choice of the hysteresis controller amplitude, poor tracking of the torque reference signal in steady state, and high torque peaks in large speed steps, which translate into current peaks that exceed the motor’s thermal limit. This work proposes new strategies for adjusting the flux and electric torque hysteresis controllers, which will correct the problems presented in the traditional implementation. Finally, a comparison will be made between the modified DTC strategy and the traditional DTC strategy of [2].

This article proposes a modified finite control set model predictive control (FCS-MPC) strategy for a three-phase three-cell flying capacitor converter implemented in two separate stages. The first one is responsible for controlling the external variables, i.e., the output current, while the second stage is responsible for the internal variables of the converter, i.e., the floating capacitor voltages, the switching losses, and the common mode voltage. The proposed implementation requires a low computational effort and offers great dynamic performance with a significant improvement in the power semiconductors switching characteristics. Experimental results in a 5-kW prototype are provided to sustain our claims.

Recently, doubly grounded (DG) photovoltaic (PV) inverters have proven superior performance in total elimination capability of PV leakage currents. This is due to the direct connection of PV side negative terminal with grid side neutral terminal. This paper presents a boost DG-PV five-level (5L) inverter topology based on neutral point clamped (NPC) leg. The proposed DG-PV boost 5L-NPC inverter totally eliminates the existing leakage currents, achieves boost of PV voltage, is considered a single stage PV inverter structure, uses low component count, and has continuous PV current. Moreover, finite control set model predictive control (FCS-MPC) is presented for controlling multiple objectives in a single cost function for the proposed topology. The FCS-MPC also eliminates the cascaded l0ops in the conventional control methods, which facilitates the control design process. A simulation based case study is preformed of the proposed DG-PV boost 5L-NPC inverter with FCS-MPC controller. Superiority of proposed inverter and controller have been verified with various step changes in PV power, power quality of injected grid current, and capacitor voltage control.

The rapid growth of smart grids necessitates advanced control strategies to ensure efficient and reliable power distribution. This paper proposes a hierarchical control framework based on Model Predictive Control (MPC) for managing power distribution in a smart grid. The hierarchical structure comprises three control levels: the first hierarchy is to control the inverter variables and the LC filter voltage, the second hierarchy supervises the power control restriction for every inverter, and the hierarchy is for power coordination, which utilizes long-term condition and prediction and power supply restriction (solar or wind capability, among other conditions or restrictions). The simulation results presented in this paper validate the fast control response and the capability of coordination between the different hierarchies of the proposed strategy.

This paper presents a novel hierarchical control scheme based on Model Predictive Control (MPC) for a Voltage Source Inverter (VSI) operating under conditions of unbalanced and nonlinear loads. The increasing prevalence of renewable energy sources and the proliferation of power electronic devices has led to a growing need for robust control strategies that can effectively handle the challenges associated with unbalanced and nonlinear loads in power distribution systems. In this work, a two-hierarchy control structure is proposed, based on a full MPC strategy. The MPC controller in the first hierarchy is responsible for optimizing the VSI's switching states in real-time, taking into account the system's constraints and the desired performance criteria of the output voltage of the VSI. The MPC controller in the second hierarchy regulates the output current of the VSI to track the reference values for the load and grid power. The proposed control scheme addresses the challenges posed by unbalanced and nonlinear loads, the simulation results demonstrate the effectiveness of the proposed hierarchical control strategy in mitigating voltage deviations, minimizing harmonic distortions, and ensuring balanced operation in the presence of unbalanced and nonlinear loads. The presented approach offers a promising solution for enhancing the performance and stability of VSI-based power distribution systems, thus contributing to the overall reliability and efficiency of modern electrical grids.

This paper proposes a Master-Slave Model Predictive Control for parallel grid-tied inverters in a microgrid. In this configuration, the Master is a grid-forming inverter with a Battery Energy Storage System as dc input, while the Slave is a grid-following PV inverter that provides the power to the load. First, the inverter models are derived and then their MPC controllers are presented in details. Finally, Hardware-in-the-Loop results are presented for different operational conditions for the microgrid, including grid connection, islanded mode and load variations. The results demonstrate the advantages of the proposed MPC such as faster dynamic response, multi variable control, adequate load sharing between the inverters, robustness to parametric uncertainties and variations and the possibility to directly include system constrains and non-linearities in the controller implementation.

Multilevel converters emerge as a promising technology for high-power medium-voltage applications due to their different advantages. On the other hand, model predictive control (MPC) is one of the control techniques that has been widely used in different applications because of its features, such as fast transient response and flexibility to include nonlinearities. The finite control set MPC (FCS-MPC) approach for a seven-level topology converter reduces the number of calculations significantly, nevertheless depends on the circuital model making it sensitive under uncertainties. On the other hand, model-free predictive control (MF-PC) has gained attention due to its accurate prediction without previous knowledge of the power system. This paper proposes MF-PC to predict the current for each phase for the seven-level topology converter. Moreover, simulation results demonstrate superior performance and feasibility of the developed control method compared to the FCS-MPC approach applied to a seven-level topology converter.

This article proposes a novel dual-stage control strategy for a flying capacitor converter. During transients, the proposed control scheme applies finite-control-set model predictive control to drive the system close to the desired reference, including all the known nonlinearities of the system in the converter model. When the converter state is in a neighborhood of the reference, the dual-stage controller switches to a pulsewidth modulation based linear controller with an integral action. In this case, the linear controller is reformulated in its feedback form. Thus, the internal linear controller states can be updated based on the actual input applied by the predictive controller. This allows the dual-stage controller to achieve a smooth transition when commuting between controllers and a zero-steady-state error even when load parameter errors are present. Experimental results are provided to verify the effectiveness of the proposed dual-stage controller.

This paper presents an improved sequential model predictive control (MPC) method for single phase photovoltaic (PV) applications. The T-type H-bridge five-level topology is selected in this paper. The proposed method achieves constant switching frequency operation of the inverter, which is advantageous over the variable switching frequency MPC methods. The proposed fixed switching frequency MPC (FSF-MPC) method eliminates the weighting factors, which represent critical element in applying classical MPC methods. Moreover, the proposed FSF-MPC method achieves low dv/dt values through using optimized switching sequences to evaluate the cost function. The simulation results of the proposed FSF-MPC method are provided and compared with variable switching frequency MPC method. The results show the fast tracking in both controllers. Whereas, fixed switching frequency and weighting factorless operation are obtained using the proposed FSF-MPC method. Additionally, lower total harmonic distortion (THD) in the output voltage is obtained using the proposed FSF-MPC method compared to classical MPC method.

This paper proposed a modulation strategy for a hybrid converter, composed by a n-cell Flying Capacitor Converter (FCC) and a classical two-level inverter. The balancing of the inner capacitors is done with logical circuits, while current control is performed with the Optimal Switching Sequence MPC. The simulation results show a good dynamic performance and an improvement of the harmonic spectrum is presented, compared to the classic two-level inverter.

Transformerless photovoltaic (PV) inverter topologies have proven superior performance over transformer-based inverter topologies. However, they face challenges due to their high leakage currents and voltage step-up requirements. There-fore, modified topologies and/or modulation techniques are essential to limit the current leakages to standard limits. The doubly grounded (DG) inverter topologies represent efficient solutions for totally limiting the leakage currents. This paper presents a finite control set (FCS) model predictive controller (MPC) method for DG step-up five-level PV inverter topology. The proposed FCS-MPC method can control the injected grid currents and multiple capacitors voltages simultaneously with high power quality output. The modelling and design of the step-up inverter topology and the FCS-MPC method are given in the paper. Simulation results with step-up DG five-level PV inverter topology are performed to validate the proposed FCS-MPC method. Moreover, the proposed FCS-MPC method has been validated using simulation results at the various operating conditions of PV inverters.

Leakage currents represent critical issues for the operation of conventional photovoltaic (PV) inverter topologies. Recently, the common grounded (CG) PV inverter topologies have presented superior performance over the conventional PV inverter topologies from the leakage currents elimination point of view. The multilevel CG-PV inverter topologies combine both features of the multilevel output voltage and the CG connection. Among the existing CG topologies, the switched capacitor types have found wide applications due to the lower cost, volume, and losses on the passive inductors. However, burdens have been risen for the control system to achieve multi-objectives, which includes controlling the output current of the inverter and the capacitor voltages. Therefore, this paper presents a Finite Control Set Model Predictive Control (FCS-MPC) method for five-level CG single-phase PV inverter topology. The FCS-MPC method presents reduced harmonic contents of the output currents and precise tracking to its reference value. The design guidelines of the FCS-MPC method and weighting factor adjustments are provided in this paper. Simulation results are presented in order to validate the effectiveness of the FCS-MPC method.

This paper proposes a horizon-one constrained model predictive control (MPC) with integral action for dc-dc H-bridge converters. An integral-action MPC law is analytically derived. The proposed controller takes into account the bilinear dynamics of the converter both in the control law derivation and constraints modeling. In addition, the proposed cost function does not presume the knowledge of the equilibrium point. In this paper, a three-level H-bridge converter for regulation purposes is considered to illustrate the proposed approach, though it is applicable to other dc-dc converter topologies as well. The paper compares the performance of the proposed analytical MPC law and the solution provided by an iterative optimisation algorithm. Simulation results are provided to verify the theoretical predictions, that is, the control law rejects constant disturbances while satisfying the designed constraints.

This paper proposes a new topology with reduced switch count for a regenerative flying capacitor multilevel inverter. This paper also introduces a new control strategy, the use of Predictive Control. The resulting control scheme is extremely simple to understand and to implement. In addition, simulation results present a very good performance of the converter.

A new multilevel converter topology is proposed in this paper. Low component count and compact design are the main features of the proposed topology. Furthermore, the proposed converter is a capacitor-, inductor-, and diode-free configuration, allowing reducing the converter footprint, increasing the lifetime and simplifying the control strategy. Further, a comparative study is carried out to highlight the merits of the proposed circuit as compared to existing multilevel topologies. Finally, simulation results for the three-level version using different modulation strategies are presented.

This paper proposes a Modulated Model Predictive Control (M2PC) algorithm for the three-phase Packed-U-Cells, PUC5, converter, that aims to minimize the output current error and balance the voltages of the DC bus capacitors. In order to do so, two cost functions are defined. The first one selects the sector in the SV diagram that minimizes the output current error, not taking into account the redundancies of the converter voltage vectors. After this, a second cost function for balancing the DC bus capacitor voltages is evaluated, considering only the voltage vectors of the chosen sector, including their redundancies. In this way, the proposed M2PC results in output voltages with fixed switching frequency, having a positive impact on the design of the output filter. Simulation results are shown, comparing the proposed M2PC and the standard variable frequency MPC strategies in terms of output current and voltage, internal capacitor voltage balancing and harmonic content.

The direct matrix converter (MC) is a promising converter that performs direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful control strategy for power electronic converters including the MC. However, weighting factor design and heavy computational burden impose significant challenges for this control strategy. This paper investigates the sequential MPC (SMPC) for a three-phase direct MC. In this control strategy, each control objective has an individual cost function and these cost functions are evaluated sequentially based on priority. The complex weighting factor design process is not required and the computational burden can be reduced. In addition, specifying the priority for control objectives can be achieved. A comparative simulation study with standard MPC is carried out in Matlab/Simulink. Control performance is compared to the standard MPC and found to be comparable. Simulation results verify the effectiveness of the proposed strategy.

Finite Control Set Model Predictive Control (FCS-MPC) allows to deal with non-linearities of the system and obtain a fast dynamic response. Therefore FCS-MPC is a good alternative to govern complex power converters or when fast transient operation is required. A problem about the implementation of FCS-MPC is the computational cost, which is bigger for multilevel converters. This paper proposed a new method to implement FCS-MPC reducing the necessary iterations in a 3-phase 4-level Flying Capacitor converter. Simulation results show that the proposed FCS-MPC strategy produces an effective control of the load current, while keeping balanced capacitor voltages with lower necessary iterations.

Multilevel converters have many advantages in power electronics. In particular, the Flying Capacitor (FC) converter is an attractive choice as it can generate high quality output waveforms and reach high power levels. Several works have been presented in the literature for voltage capacitor balancing, relying on self-balancing property. Nevertheless, the conditions for self-balancing operation cannot be guaranteed in several practical applications. In this paper, a simple closed-loop scheme, based on Model Predictive Control (MPC), is used to properly modulate the converter output voltage in order to keep the capacitor voltages at the desired values. As the proposed modulation strategy regulates the capacitor voltages, wide bandwidth linear controllers can be used for the current tracking, improving the dynamic and steady-state behavior of the overall system.

Multilevel converters are an attractive alternative for medium voltage applications. The Stacked Multicell Converter (SMC), in particular, is a multilevel converter that allows to increase the output voltage level compared with the classical Flying Capacitor Converter, while decreasing the stored energy in the converter. This paper presents the application of Finite Control Set Model Predictive Control (FCS-MPC) in a three phase SMC with two cells and two stacks. The strategy controls simultaneously the load currents and capacitor voltages. simulation results show that the FCS-MPC strategy produces an effective control of the load current, while keeping balanced capacitor voltages. In addition, it is demonstrated that FCS-MPC outperforms Phase Shifted Pulse Width Modulation with linear controllers in transient and steady state operation.

Multilevel converters are an attractive alternative for medium voltage applications. The Stacked Multicell Converter (SMC), in particular, is a multilevel converter that allows to increase the output voltage level compared with the classical Flying Capacitor Converter, while decreasing the stored energy in the converter. This paper presents the application of Model Predictive Control (MPC) in a three phase SMC with three cells and two stacks (3×2). The strategy controls simultaneously the load currents and capacitor voltages. A problem about the implementation of MPC is the computational cost, which is bigger for multilevel converters. In the case of SMC 3×2 it is necessary to do 19683 iterations, for This paper proposed a new method to implement MPC reducing the necessary iterations from 19683 to 343. Simulation results show that the proposed MPC strategy produces an effective control of the load current, while keeping balanced capacitor voltages and lower THD that classical MPC with 57.38 times lower iterations.

In this work, we propose a dual-stage control approach for a three-phase four-level Flying Capacitor Converter. The key idea of this proposal is to combine two control strategies to govern this converter. Thus, if the system state (output currents and floating voltages) is far from the desired reference, Finite-Control-Set Model Predictive Control is used to quickly lead the system towards the reference. Once the system state reaches a neighborhood of the reference, the propose control strategy switches to a PWM-based linear controller to finally achieve the desired reference in a gentle manner.