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This paper presents an experimental implementation of a predictive control strategy for a system made up of two induction machines fed by a six-leg indirect matrix converter. The objective is to evaluate the practical feasibility of this method, considering the large computational cost, and to incorporate available market technologies. This strategy achieves tracking of torque, speed, and flux references on both machines, minimizing the instantaneous input reactive power present in the system. A theoretical explanation of the main concepts that are used in the predictive control strategy is presented, along with comments on the experimental implementation, experimental setup, and results obtained under both balanced and unbalanced grid conditions. [ABSTRACT FROM PUBLISHER]

Predictive control represents an optimization-oriented alternative for the control of power converters and drives. Predictive torque control of induction machines has been shown to achieve excellent initial results. The objective of this paper is to help develop this promising control approach by introducing new elements to improve its performance. The resulting algorithm improves the efficiency of the converter from \91.1\% to \92.6\% and achieves a common-mode voltage mitigation of \50\%, compared to the basic control method. A tradeoff is observed in the power quality. The algorithm gives the designer the ability to select the best operating point for each particular application and to optimize the converter’s performance. Experimental results are presented to validate the proposals. [ABSTRACT FROM PUBLISHER]

Multilevel converters can reach medium-voltage operation increasing the efficiency of high-power applications. Among the existing multilevel converter topologies, the modular multilevel converter (MMC) provides the advantages of high modularity, availability, and high power quality. Moreover, the main advantage compared to cascaded multilevel converters is the lack of an input transformer which results in a reduction of cooling requirements, size, and cost. One of the drawbacks of this topology when used as an ac–ac converter is the input and output frequency components in the control loop, resulting in a more complex controller design. In this paper, a single-phase ac–ac MMC predictive control approach is proposed. The controller minimizes the input, output, and circulating current errors and balances the dc voltages. Experimental results show the performance of the proposed predictive control scheme. [ABSTRACT FROM PUBLISHER]

A predictive control scheme for the indirect matrix converter including a method to mitigate the resonance effect of the input filter is presented. A discrete-time model of the converter, the input filter, and the load is used to predict the behavior of the instantaneous input reactive power and the output currents for each valid switching state. The control scheme selects the state that minimizes the value of a cost function in order to generate input currents with unity power factor and output currents with a low error with respect to a reference. The active damping method is based on a virtual harmonic resistor which damps the filter resonance. This paper shows 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]

This paper presents a review of the most popular control and modulation strategies studied for matrix converters (MCs) in the last decade. The purpose of most of these methods is to generate sinusoidal current on the input and output sides. These methods are compared considering theoretical complexity and performance. This paper concludes that the control strategy has a significant impact on the resonance of the MC input filter. [ABSTRACT FROM AUTHOR]

When control schemes based on finite control set model predictive control are experimentally implemented, a large amount of calculations is required, introducing a considerable time delay in the actuation. This delay can deteriorate the performance of the system if not considered in the design of the controller. In this paper, the problem is described, and the solution to this issue is clearly explained using a three-phase inverter as an example. Experimental results to validate this solution are shown. [ABSTRACT FROM PUBLISHER]

The aim of this article is to develop a real-time computational method that determines switching angles of selective harmonic elimination (SHE) for operating nine-level (9 L) current-fed multilevel converter (MLC). The computation algorithm for SHE conventionally requires huge calculation time to identify switching angles of the inverter, and hence, a truth table based modulation is applied for operating the converter in real time. To overcome this, a new analytical method has been proposed in this article that minimizes the computation time to calculate the switching angles. However, these switching angles cannot be directly applied to current-fed MLCs. Unlike voltage fed converters, the current-fed converters have additional operational constraints on the modulation technique. Hence, in this article, a conversion technique has been utilized to convert the unconstraint SHE angles into constraint angles in order to operate current-fed MLCs. A low-power prototype of 9 L current source inverter has been set-up to experiment and validate the proposed real-time calculation method at the fundamental frequency of 50 Hz. [ABSTRACT FROM AUTHOR]

The finite control set model predictive control (FCS-MPC) for power electronic converters provides high dynamic performance, based on the limited number of inputs and accurate model of the converter. By applying this algorithm to multilevel converters such as a cascaded-H-bridge-based static var compensator (CHB STATCOM), the dynamic performance is degraded, because the optimized input is achieved by searching among a large set of switching combinations and redundancies. This paper proposes an FCS-MPC algorithm, which benefits high dynamic performance for the CHB STATCOM, despite the large set of inputs. The proposed FCS-MPC replaces the time-consuming optimization algorithm by solving Diophantine equations over the large set of switching combinations. The desired switching combination and all its redundancies are determined in a minimum execution time. The proposed FCS-MPC performance is validated by applying to two configurations: 1) a 15-level CHB STATCOM with energy storage capability for a short-term active power smoothing and reactive power compensation of a 10 MW fixed speed wind farm at medium voltage; and 2) an experimental seven-level CHB STATCOM at low voltage. [ABSTRACT FROM AUTHOR]

Finite control set-model predictive control (FCS-MPC) is emerging as an attractive alternative for power converters control. In comparison with the classical linear controllers, FCS-MPC needs a shorter control loop cycle time to achieve the same performance. But, the conventional FCS-MPC involves a large amount of calculation. The calculation efforts increase with the number of switching states of the power converter as well as the control objectives, which is a challenge for its application. This paper proposes an effective method to simplify the FCS-MPC and to reduce its calculation efforts for its application in matrix converter-fed permanent magnet synchronous motors. The experimental results which verify the good performance of the proposed method are presented. [ABSTRACT FROM PUBLISHER]

Predictive torque control (PTC) is based on the prediction of motor torque and stator flux for all possible voltage vectors of power converter. These predictions are derived from a mathematical model of the motor that depends on the motor parameters. But, these parameters may not match with their actual values. These parametric uncertainties lead to inaccurate predictions of torque and stator flux and affect the performance of the predictive algorithm. This paper presents a modified PTC for a permanent magnet synchronous motor to reduce the torque ripple at the presence of parametric uncertainty by improving the prediction accurateness. Simulation and experimental results are provided to show the effect of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper presents the experimental validation of a predictive current control strategy with minimization of the instantaneous reactive input power for a Four-Leg Indirect Matrix Converter (4Leg-IMC). The topology includes an input matrix converter stage, which provides the dc voltage for a four-leg voltage source converter (VSC) output stage. The VSC's fourth leg provides a path for the zero sequence load current. The control technique is based on a finite control set model predictive control (FCS-MPC) strategy, whereby the switching states for the input and output converters are selected by evaluating a predictive cost function. This results in a simpler approach than that seen in other well-known modulation methods, such as three-dimensional space vector modulation (3D-SVM). Positive dc voltage, (a requirement for the safe operation of the IMC) and minimization of the instantaneous input reactive power are obtained, while maintaining good tracking of the load reference currents. Furthermore, soft switching is achieved by synchronizing the state changes in the input stage with the application of zero voltage space vectors in the inverter stage. The control strategy is experimentally verified using a laboratory prototype. [ABSTRACT FROM AUTHOR]

Three-phase voltage source inverters (VSIs) with output $ LC$ filter are preferred topologies to provide voltage and frequency support for islanded ac microgrids. This article proposes a finite-set quasi-sliding model predictive control (FS-QSMPC) scheme for $LC$ -filtered VSIs to improve the output-voltage quality. By explicitly including a predictive sliding-mode function into the cost function, reduced steady-state ripple and enhanced robustness are achieved compared to typical FS-MPC. Besides, theoretical analysis of stability and robustness for FS-QSMPC is given. Analytical tuning of the weighting factor is also derived to decrease the tuning effort. Comparative simulations and experiments verify the presented approach. [ABSTRACT FROM AUTHOR]

This article proposes a fixed switching frequency (FSF)-based improved model predictive control (MPC) for a five-level active neutral-point clamped (5L-ANPC) converter. Compared to the conventional MPC for 5L-ANPC converter, the proposed MPC significantly reduces the computational burden while ensuring the balance of dc-link and flying capacitor voltages. The proposed MPC optimally selects the control voltage vectors to reduce common mode voltage (CMV), leading to a small CMV of the converter. Using three voltage vectors action per control cycle in MPC, FSF is achieved. Steady-state and dynamic performances of the proposed MPC have been evaluated by experiments. The results verify the feasibility and effectiveness of the proposed MPC method. [ABSTRACT FROM AUTHOR]

This letter proposes a data-driven iterative learning predictive control architecture for power converters. The main objectives of this letter are to enhance the robustness and remain the high performance of finite control-set model predictive control (FCS-MPC) under unmodeled dynamics and parameter mismatch conditions. More specifically, an iterative dynamic linearization technique is utilized to equivalently reformulate the nonlinear power converter system at each operating point. Based on this, a model-free adaptive control scheme is presented to iteratively determine the optimal control actions. Due to the incorporation of iterative learning control and data-driven concept into the FCS-MPC framework, the effect of parameter perturbations can be alleviated in the proposed method, while creating a positive effect on the tracking error. Finally, a convergence analysis is provided and experimental investigations on a three-level neutral-point-clamped (NPC) converter confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Multisource switched-capacitor multilevel inverters are proper topologies when multiple dc sources are available as renewable energy sources. However, these multilevel inverters have the main drawbacks of requiring a large number of power semiconductors and capacitors and a low boost factor to achieve a large number of voltage levels, which complicate control, reduce performance, and raise the cost. This article presents two configurations for multisource switched-capacitor multilevel inverters. First, a basic multisource switched-capacitor topology is proposed with a small number of capacitors and semiconductors that produce a zero voltage level and a large number of positive voltage levels. The input dc sources are operated in an asymmetric trinary algorithm, while the capacitors are charged/discharged in a binary algorithm using parallel/series modes (without the need for any circuit balancing). Based on the proposed basic topology, two multilevel inverter topologies are proposed, which create bipolar output voltage levels using two different circuits at the output. The first proposed topology uses a standard H-bridge inverter at the output of the basic topology, while the second topology uses an extra switched-capacitor (self-balancing) circuit. The comparison indicates that both the proposed topologies have advantages over most of the reported multisource switched-capacitor multilevel inverters, such as a small number of capacitors, a small number of power semiconductors, low voltage stress, and high boost factor. Furthermore, the proposed topologies decrease the low cost factor in comparison to other topologies. The capacitors' capacitance, power losses, and voltage ripple losses are all measured and evaluated in detail. Theoretical research is validated with the use of laboratory prototypes to validate the performance of the proposed topologies. [ABSTRACT FROM AUTHOR]

A fault-tolerant control (FTC) is proposed for enhancing the reliability of power electronic systems. The software-based FTC of parallel-connected three-level T-type converters (3LT2Cs) for suppressing zero-sequence circulating current (ZSCC) induced by a vertical switch open-circuit fault is investigated. A simplified sequential model predictive control (SSMPC)-based FTC technique is developed. Parallel-3LT2Cs and their prediction models are introduced, followed by an SSMPC for the no-fault condition. The model inaccuracies under vertical switch faults are elaborated. For the faulty 3LT2C, two fault-tolerant SSMPC (FT-SSMPC) methods are provided by creating a sequential predictive controller that considers ZSCC suppression and grid current tracking. The control policies for the ZSCC are changed from the standard feedback-free to feedback-based cost function (CF) optimization using the unimproved FT-SSMPC. Furthermore, an improved FT-SSMPC is proposed using a phase-deficient CF, which increases the accuracy of the mathematical relation of the fault condition. After fault diagnosis, the proposed method achieves neutral-point voltage balance and excellent point-of-common-coupling current, effectively suppresses the ZSCC, and increases the control reliability. Finally, experiments demonstrate the effectiveness of the proposed FT-SSMPC under various conditions. [ABSTRACT FROM AUTHOR]

Recently, fault-tolerance control (FTC) methods have been proposed to further improve the reliability of T-type three-level converters. However, the application of model predictive control (MPC) in FTCs is rare, and the neutral point (NP) voltage imbalance before an open-switch fault occurs has not been solved. This article focuses on these two problems and proposes two FTC control methods: sequential MPC and sequential model predictive tolerance control. Both methods are implemented by designing a sequential predictive control that first considers the NP voltage balance and then grid current tracking. Through the staggered operation of the two methods, a T-type grid-connected converter with an LCL filter can operate normally after an open-switch fault occurs. Moreover, both methods can achieve the NP voltage balance and excellent grid current outputs, eliminate the time-consuming selection of weighting factors, and reduce the number of calculation loops compared with the traditional model predictive tolerance control, thereby improving the control flexibility. The performance and comparison of the open-switch FTC with respect to the NP voltage oscillations, total harmonic distortion of the grid current, and pole voltage were demonstrated using numerous simulation and experimental results. [ABSTRACT FROM AUTHOR]

In this article, a low-cost multistep finite control set model predictive current control (FCS-MPCC) using a dc link single current sensor is proposed for permanent magnet synchronous motor (PMSM). In order to reduce the system cost, the single dc link current sensor is used to reconstruct the three-phase current. Different from the current reconstruction technology of field-orientated control strategy, there are some problems of the existed current reconstruction technology applied for finite control set model predictive control (FCS-MPC). First, the optimal switching state of FCS-MPC in each cycle is not fixed, and only contains at most one phase current information for reconstruction, which will cause the reconstruction failure. Therefore, a multiperiod sampling method is proposed to obtain the different two-phase current information to reconstruction. Second, the uncertainty of the two-phase reconstruction current interval will lead to current error, so this article proposes a variable period compensation method to solve this problem. Moreover, in order to improve the system closed-loop performance without significantly increasing the computational cost and enhance the system reliability, a low-cost multistep FCS-MPCC strategy based on the reconstructed three-phase current is proposed for PMSM. Finally, simulation and experimental results validate the effectiveness of the low-cost multistep FCS-MPCC method using a dc link single current sensor reconstruction for PMSM. [ABSTRACT FROM AUTHOR]

This article proposes a continuous control set predictive speed control (CCS-PSC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives, where the prediction horizon is short and the computational complexity is low. The optimization problem of the proposed CCS-PSC is formulated and analyzed. The current and voltage constraints are transformed into incremental voltage constraints, which can be updated in real-time. A reduced-order incremental model of SPMSM is adopted for the prediction, where integrators are naturally embedded. Hildreth’s quadratic programming algorithm is used to solve the optimization problem, where the active constraints are identified and the reference voltage is calculated. The performance of the proposed strategy is validated through comparative experiments with finite control set predictive speed control (FCS-PSC), cascaded CCS-PSC and field-oriented control. The results demonstrate the superb dynamic performance of the proposed CCS-PSC strategy, while the phase current total harmonic distortion is relatively low. [ABSTRACT FROM AUTHOR]

With the increasing penetration of distributed energy resources into islanded microgrids, a grid-forming inverter (GFI) has become the key element interfacing renewable energy sources. Usually, the GFI is employed with an output filter to minimize the harmonic content achieving high-quality output voltage regulation. To this end, model-predictive control (MPC) has been widely proposed to control the output voltage of GFI systems due to the high-quality performance, fast control response, and straightforward handling of constraints. However, an accurate model of the system is required for the conventional MPC to avoid a suboptimal performance under uncertainties. To overcome this known drawback, a novel model-free predictive control is proposed in this article. Consequently, the output voltage of an $LCL$ -filtered GFI is regulated without the knowledge of the physical model. [ABSTRACT FROM AUTHOR]

Three-level T-type converters (3LT2C) with inductance–capacitance–inductance filters have high power quality of grid current, particularly in the low-voltage system. However, the switching loss and conduction losses degrade the overall efficiency of 3LT2C. The generated heat due to the losses endangers the reliability of the device and shortens its service life. To relieve the power losses as well as maintain high-quality current output, a low-loss-tolerant sequential model predictive control (LL-TSMPC) is proposed. First, based on the energy loss analysis under switching transitions per commutation, the prediction models of both switching loss and conduction loss are established. Second, the total loss reduction is considered as one control objective in LL-TSMPC. Finally, because multiobjective model predictive control (MPC) requires selecting appropriate weighting factors, complicating the design to solve this problem, TSMPC-based lexicographic optimization is introduced to eliminate the tradeoff factors and simplify the MPC controller design. The proposed method is tested on the hardware platform with the rated power of a 10-kW prototype. The experimental results show that the LL-TSMPC method can effectively reduce the switching losses while maintaining the high power quality of the grid current. [ABSTRACT FROM AUTHOR]

This article presents a generalized simplified virtual vector pulsewidth modulation (SVVPWM) to attain the capacitor voltage balancing of multilevel diode-clamped converter (DCC) for all operational conditions, which is not possible by using conventional space vector pulsewidth modulation (PWM) and carrier-based PWM methods. Virtual vector PWM is a solution presented in the literature to sort out this issue but it becomes more complex for higher level converters. The proposed SVVPWM method is simple and easy to implement for any level converter because it converts the space vector (SV) diagram of any level converter to three-level SV diagram. The SVVPWM assures the natural voltage balancing under steady states and ideal operations. Under dynamic operations, a generalized equation that describes the influence of neutral point currents on dc-link capacitor's voltage has been derived and a general decoupled voltage balancing control for n-level DCC is presented. The proposed modulation method is implemented on five-level and seven-level DCCs to authenticate the effectiveness of decoupled voltage balancing control. Simulation and experimental results demonstrate that the proposed modulation strategy is easy to implement and effectively controls the balance of the capacitor voltages for the whole range of modulation index and load power factor. [ABSTRACT FROM AUTHOR]

Sliding-mode control (SMC) has been widely used in grid-connected converter system (GCC) systems because of its robustness to parameter variations and external disturbances. However, chattering in SMC may deteriorate the tracking accuracy and can easily excite high-frequency unmodeled dynamics. To solve this problem, this article presents a fuzzy-fractional-order nonsingular terminal sliding-mode controller (Fuzzy-FONTSMC) for the grid current control of LCL–GCCs. First, the system modeling, design of the integer-order NTSMC controller, and state estimation based on the Kalman filter to minimize the sampling sensors are described. Second, the Fuzzy-FONTSMC controller is introduced for optimal fraction-order selection and chattering mitigation, this controller exhibits fast convergence with high tracking accuracy and strong robustness. Finally, the Lyapunov theorem is used to analyze the system stability. Experimental comparisons on a 10-kVA laboratory prototype validate the superior performance and effectiveness of the proposed method under many scenarios. [ABSTRACT FROM AUTHOR]

Fault-tolerant control (FTC) strategies have been proposed to improve the reliability of power electronic systems. However, the FTC of the three-level T-type converter based shunt active power filter (SAPF) remains limited by redundant devices. To address this problem, an FTC strategy called sequential model predictive tolerant control (SMPTC) is combined with a nonintegral lexicographic optimization (LO) algorithm for solving multiobjective optimization problems. First, the power circuit, space voltage vector diagram, harmonic extraction, and prediction models of the SAPF system are introduced. Second, based on power-switch fault analysis, an adaptive dc bus voltage regulation method is proposed, which ensures that the candidate voltage vectors are fully utilized in the fault state. Third, an LO-SMPTC strategy is proposed by designing a sequential predictive controller that considers the neutral point (NP) voltage and the tracking of the SAPF output current. Compared with the traditional model predictive control, the proposed method not only achieves NP voltage balance and excellent harmonic compensation but also eliminates the selection of weighting factors, thereby improving the control flexibility and time efficiency. Finally, the effectiveness of the LO-SMPTC on the dc bus voltage, NP voltage oscillations, grid current power quality, and pole voltage under different scenarios is demonstrated through experiments. [ABSTRACT FROM AUTHOR]

Finite control set model predictive control (FCS-MPC) has been widely recognized in the field of electrical drive control during the past decades, due to its merits of quick dynamic response and low switching frequency. However, it is inherently penalized by high tracking deviations in the steady-state as well as exhaustive search among the switching sequences. To cope with this issue, a low-complexity gradient descent-based finite control set predictive current control (GD-FCSPCC) combined with a backtracking iteration approach is proposed in this article, aiming to improve the control performance by effectively tracking the reference value. First, FCS-PCC is reformulated as a quadratic programming (QP) problem from a geometric perspective. Consequently, the convexity of QP problem is proved to underlying the gradient descent, which minimizes the tracking deviations in an effective manner. Thus, the optimal solutions are selected by optimizing the reformulated objective functions. To reduce the number of the searched control inputs, a two-layer generalized decision-tree is employed. The procedures are repeated in several iteration periods optimized via a backtracking method, until the stopping criterion is satisfied. The effectiveness of the proposed GD-FCSPCC is experimentally validated on a 2.2 kW induction machine testbench. [ABSTRACT FROM AUTHOR]

Modular multilevel converters have several attractive features such as a modular structure, the capability of transformer-less operation, easy scalability in terms of voltage and current, low expense for redundancy and fault tolerant operation, high availability, utilization of standard components, and excellent quality of the output waveforms. These features have increased the interest of industry and research in this topology, resulting in the development of new circuit configurations, converter models, control schemes, and modulation strategies. This paper presents a review of the latest achievements of modular multilevel converters regarding the mentioned research topics, new applications, and future trends. [ABSTRACT FROM AUTHOR]

There has been an increasing interest in using model predictive control (MPC) for power electronic applications. However, the exponential increase in computational complexity and demand of computing resources hinders the practical adoption of this highly promising control technique. In this article, a new MPC approach using an artificial neural network (termed ANN-MPC) is proposed to overcome these barriers. A power converter with a virtual MPC controller is first designed and operated under a circuit simulation or power hardware-in-the-loop simulation environment. An artificial neural network (ANN) is then trained offline with the input and output data of the virtual MPC controller. Next, an actual FPGA-based MPC controller is designed using the trained ANN instead of relying on heavy-duty mathematical computation to control the actual operation of the power converter in real time. The ANN-MPC approach can significantly reduce the computing need and allow the use of more accurate high-order system models due to the simple mathematical expression of ANN. Furthermore, the ANN-MPC approach can retain the robustness for system parameter uncertainties by flexibly setting the input elements. The basic concept, ANN structure, offline training method, and online operation of ANN-MPC are described in detail. The computing resource requirement of the ANN-MPC and conventional MPC are analyzed and compared. The ANN-MPC concept is validated by both simulation and experimental results on two kW-class flying capacitor multilevel converters. It is demonstrated that the FPGA-based ANN-MPC controller can significantly reduce the FPGA resource requirement (e.g., 2.11 times fewer slice LUTs and 2.06 times fewer DSPs) while offering a control performance same as the conventional MPC. [ABSTRACT FROM AUTHOR]

In this article, an efficient model predictive control (MPC) using virtual voltage vectors for three-phase three-level converters is proposed. The proposed MPC achieves constant switching frequency by applying four voltage vectors, including one virtual voltage vectors and three other voltage vectors, in each control cycle. In addition, to reduce the computational burden, two-stage MPC approach is adopted. The first stage chooses one of six medium voltage vectors that minimizes the cost function. Then, in the second stage, these voltage vectors including virtual voltage vectors, which locate the same sector with the optimal medium voltage vector, are involved in the MPC optimization. The advantages of the proposed MPC over the classical MPC have been validated through experimental results. [ABSTRACT FROM AUTHOR]

Aging and temperature changes in the passive components of an LCL-filter grid connected converter system (GCCs) may lead to parameter uncertainties, which can in turn influence its modeling accuracy for finite-control-set model predictive control (FCS-MPC). The presence of model errors will change the resonance point and deteriorate the power quality of the grid current, in turn degrading the active damping performance. In this situation, there is a serious possibility that the GCCs may malfunction and automatically disconnect from the grid, causing great challenges to the system stability. To solve this problem, first, prediction error analysis in FCS-MPC due to the model parameter errors is presented. Second, to achieve high accuracy and fast filter parameter estimation in utility, an adaptive online parameter identification method based on gradient descent optimization (GDO) has been proposed. Finally, to further reduce the searching time needed by the optimal iteration step, a variable iteration step searching method based on the root-mean-square-prop (RMSprop) GDO method is proposed. Experimental studies of an LCL-GCCs prototype in the laboratory have been conducted to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The series connection of a standard three-level active neutral-point-clamped (ANPC) inverter and two cascaded H-bridge (CHB) modules comprising the flying capacitors (FCs) instead of the isolated dc voltage sources forms a seven-level hybrid topology that is referred to as improved ANPC (I-ANPC) converter. This article proposes an active voltage balancing technique for control of this hybrid multilevel inverter. The suggested method is based on a set of effortless logic equations that aim to stabilize the FC voltages within the CHB modules at their requisite reference values as well as to control the output voltage of the overall hybrid converter based on the phase-shifted-carrier pulsewidth modulation strategy. The experimental results obtained from a single-phase I-ANPC inverter's prototype are presented to validate the proposed control technique and its simple logic equations. [ABSTRACT FROM AUTHOR]

An improved two-stage model predictive current control (MPCC) for three-phase three-level converters in the paper, which can simultaneously achieve common-mode voltage (CMV) reduction, effective dc-link capacitor voltage control, and decreased computational burden, is proposed. Compared to the other current control strategies, it has the capability of handling multiple control objectives and possesses a simple structure. Furthermore, it greatly reduces the CMV since the peak CMVs of all the candidate voltage vectors are constrained to be less than one sixth of the dc-link voltage. In addition, an optimal two-stage voltage vector selection mechanism is employed in the proposed method. It helps to significantly reduce the computational complexity. Simulation and experimental results are provided to verify the effectiveness of the proposed method. [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]

This paper presents first an overview of the well-known voltage and current dc-link converter topologies used to implement a three-phase PWM ac–ac converter system. Starting from the voltage source inverter and the current source rectifier, the basics of space vector modulation are summarized. Based on that, the topology of the indirect matrix converter (IMC) and its modulation are gradually developed from a voltage dc-link back-to-back converter by omitting the dc-link capacitor. In the next step, the topology of the conventional (direct) matrix converter (CMC) is introduced, and the relationship between the IMC and the CMCs is discussed in a figurative manner by investigating the switching states. Subsequently, three-phase ac–ac buck-type chopper circuits are considered as a special case of matrix converters (MCs), and a summary of extended MC topologies is provided, including three-level and hybrid MCs. Therewith, a common knowledge basis of the individual converter topologies is established. [ABSTRACT FROM PUBLISHER]

A drive topology composed of a T-type single-phase three-level voltage source rectifier (VSR) and a four-level switched reluctance motor (SRM) converter is proposed in this article. The commonly used diode bridge rectifier presenting degraded power quality is replaced by the VSR to drive the SRM converter. Compared with the conventional split-dc converter, the four-level SRM converter of the proposed drive topology adopts one more switch and one more diode for each phase, but two more operation modes are formed. With the double-voltage demagnetization mode of the four-level SRM converter, the tailing time of demagnetization current is significantly reduced, which increases the utilization of inductance increasing region. All the operation modes of this converter can be implemented successfully, even in the multiphase excitation region. Moreover, a centralized control strategy is proposed to regulate the VSR and SRM together, within which the speed and grid-side power factor are regulated by the d-axis and q-axis component of grid-side current in VSR, respectively. Most importantly, the bidirectional energy flow is realized. An idea-proofed testbench is constructed. The results obtained from the comparative experiments confirm the validity of the proposed drive topology and its control strategy. [ABSTRACT FROM AUTHOR]

Conventionally, the converter of switched reluctance motor (SRM) is fed by the uncontrollable diode bridge rectifier (DBR), which leads to a low grid-side power factor (PF) and high current total harmonic distortion (THD). In this paper, an alternative solution for the grid-connected high-speed SRM drive system with improved PF is proposed. In the proposed drive system, the three-level active front end (AFE) is connected in cascade with the midpoint converter for SRM operation. A centralized strategy, which controls the AFE and SRM together, is proposed to govern the motor speed and grid-side PF by regulating the real power and reactive power of the system, respectively. Specifically, the real power, reactive power, and the voltage balancing of split capacitors are controlled by the model predictive directed power control (MP-DPC) algorithm, which significantly reduces the control complexity and guarantees the fast dynamic response. Consequently, satisfying speed regulation, high PF, low current THD, and bi-directional power-transfer capability are achieved. An idea-proofed testbench is constructed in laboratory, and the applicability of the proposed drive system is verified by a series of experimental results. [ABSTRACT FROM AUTHOR]

In this article, a novel multilevel topology for three-phase applications, having three-level and hybrid N-level modular configurations, enabling low-, medium-, and high-voltage operations, is presented. The proposed topology has several attractive features, namely reduced component count, being capacitor-, inductor-, and diode-free, lowering cost, control-complexity, and size, and can operate in a wide range of voltages and powers. Selected simulation and experimental results are presented to verify the performance of the proposed topology. Further, the overall efficiency of the topology and loss distribution in switches are studied. Finally, the key features of the proposed topology in terms of component count, blocking voltage, and dc-link requirements are highlighted via a comparative study. [ABSTRACT FROM AUTHOR]

The efficiency of the linear induction machine (LIM) is considerably low due to the large air-gap length and the additional losses resulting from the end-effects. However, so far, a little concentration has been done to increase the efficiency of this kind of motor. Therefore, the main objectives of this article are to eliminate the weighting factor, reduce the calculation steps, and increase the efficiency of the LIM aiding with a proposed finite-set model predictive direct flux control (FS-MPDFC), depending upon the maximum thrust per ampere (MTPA) strategy. The proposed FS-MPDFC is only based on the primary flux-linkage with the help of a novel cost function that does not require any weighting factors in order to considerably reduce the calculation steps. Moreover, the proposed FS-MPDFC is better than the model predictive current control in reducing the calculation step and decreasing the dependence on the transformation matrix and the machine parameters. In order to illustrate the effectiveness of the proposed MTPA-based FS-MPDFC, a comparison between the FS-MPDFC, with and without MTPA, and the previously suggested control techniques is presented and discussed. Moreover, a test bench platform of two 3-kW arc induction machines is constructed to emulate the drive performance of the actual LIM. Comprehensive simulation and experiments have fully demonstrated that the proposed FS-MPDFC with MTPA has lower calculation step, lower thrust ripple by 7%, and lower primary flux-linkage ripple by 0.4% compared to those of the FS-MPDTC. Moreover, the efficiency-based FS-MPDFC with MTPA is increased by 4% compared to that of the FS-MPDFC without MTPA. [ABSTRACT FROM AUTHOR]

Voltage source inverters with output LC filter enable a sinusoidal output voltage with low harmonics, suitable for islanded ac microgrid or uninterruptible power supply applications. Conventional finite-set model predictive voltage control (MPVC) applies only a single switching vector per control period, leading to a variable switching frequency and significant output ripple. This article resolves these issues by proposing an improved MPVC with optimal switching sequence (OSS-MPVC). First, an improved vector switching sequence is defined, aiming to reduce the output-voltage ripple with a constant switching frequency. Then, to tackle the difficulty in extending the OSS to high-order systems due to the coupling effect of the output filter, a generalized “one-step estimation” solution is proposed, which directly associates the control-variable gradients with the vector switching sequence. To further enhance the output-voltage tracking accuracy, intersample dynamics are taken into account in the cost function. The control delay and dead-time compensation are also considered. Simulations and experimental results verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Multilevel inverters (MLIs) have gained increasing interest for advanced energy-conversion systems due to their features of high-quality produced waveforms, modularity, transformerless operation, voltage, and current scalability, and fault-tolerant operation. However, these merits usually come with the cost of a high number of components. Over the past few years, proposing new MLIs with a lower component count has been one of the most active topics in power electronics. The first aim of this article is to update and summarize the recently developed multilevel topologies with a reduced component count, based on their advantages, disadvantages, construction, and specific applications. Within the framework, both single-phase and three-phase topologies with symmetrical and asymmetrical operations are taken into consideration via a detailed comparison in terms of the used component count and type. The second objective is to propose a comparative method with novel factors to take component ratings into account. The effectiveness of the proposed method is verified by a comparative study. [ABSTRACT FROM AUTHOR]

This article proposes a modified modulated model predictive control (M3PC) for a grid-connected converter, which features enhanced steady-state and transient performance, low complexity, and capability of multiobjective optimization. The advantages of fast dynamics and inherent overmodulation capability of finite control set model predictive control are preserved while a constant switching-frequency and improved steady-state performance are achieved. High tracking error and distortion caused by the limitation of conventional modulated model predictive control (M2PC) optimization near the hexagonal limit of voltage vectors and the sector boundaries are addressed with the proposed M3PC scheme. Experimental results verify that reduced tracking errors and lower total-harmonic distortion in grid current are achieved by the proposed method compared to the conventional M2PC scheme. It is also confirmed that the capability of overmodulation operation in the proposed method enhances transient performance and dc-bus utilization. [ABSTRACT FROM AUTHOR]

In this letter, an event-triggered model predictive control (ET-MPC) method for power converters is presented. In the proposed method, the model predictive control (MPC) scheme is triggered only when the state of the converter exceeds a preset threshold; otherwise, the MPC scheme is suspended and the control signal is held as constant. Therefore, compared with the conventional MPC with finite control set (FCS-MPC), the ET-MPC method has the advantages of less computational burden and less switching actions, which contribute to lower switching losses, while ensuring satisfactory regulation performance. A buck converter prototype is adopted to validate the performance of ET-MPC. The results from the comparison with FCS-MPC demonstrate the effectiveness of the proposed ET-MPC method. [ABSTRACT FROM AUTHOR]

Finite control set model predictive control (FCS-MPC) calculates torque and flux tracking errors via a cost function that is used for selecting the optimal vector. Compared with field oriented control, FCS-MPC has the merit of a faster dynamic performance because it eliminates both pulsewidth modulation and inner proportion-integration controllers. However, the weighting factor for modifying torque and flux terms must be tuned in accordance with varying operating conditions; this is an area in which further research is needed. In this paper, a parallel predictive torque control (PPTC) with predefined constraints is proposed as a solution for this problem. The PPTC method optimizes torque and flux terms simultaneously, and switching-state candidates are then selected in an adaptive mechanism. The key feature is that torque and flux tracking errors are constrained within the initial boundaries. The proposed PPTC is compared with the state-of-the-art predictive torque control (PTC) method. Both simulation and experimental results confirm that the proposed method, which has no weighting factor, achieves an even better dynamic performance and robustness than the conventional PTC. [ABSTRACT FROM AUTHOR]

The per-phase leg of an improved active-neutral-point-clamped (I-ANPC) multilevel converter is realized by the cascaded connection of the standard ANPC topology and the concatenated H-bridge modules consisting of the flying-capacitors (FCs). This article proposes an innovative approach for the active control of the I-ANPC inverters. The introduced methodology is developed on the basis of the logic-equations set for the active voltage balancing of the FCs within the H-bridge modules, and controlling the generated output voltage. It derives logic-variables employing the direction of the output current, and the deviation of the FCs’ voltages from their target operating levels in the H-bridge cells. These logic-variables are fed into a set of logic-equations derived for the control of the I-ANPC inverter. The regulation of the floating-capacitor voltages at their reference values along with synthesizing the required pulsewidth modulation voltage-level at the output having fast dynamics are the control objectives to achieve. The derived logic-equations and the proposed control method are explored and verified by the experimentally measured results obtained from the 5-kW prototype of a five-level converter. [ABSTRACT FROM AUTHOR]

In this work, a model predictive control (MPC) strategy based on optimal switching sequence (OSS) concepts is proposed for a grid-connected three-level neutral-point clamped converter. The proposed cascaded-OSS-MPC strategy does not require a weighting factor to balance the dc-link capacitor voltages and optimally controls both the grid currents and the capacitor voltages even during disturbances and large step changes in the references. The resulting MPC strategy allows operating the converter with a predefined harmonic spectrum, fixed switching frequency, and fast and robust dynamic response. Besides, an efficient optimization algorithm is also introduced to reduce the computational burden typically observed in this kind of MPC strategies. Experimental and simulation results are provided to demonstrate the effectiveness and high-quality performance of the proposed strategy. [ABSTRACT FROM AUTHOR]

As cascaded proportional-integral controllers involve complicated tuning work, many efforts have been focused on direct controllers. Direct torque control and predictive torque control are both feasible solutions. However, bigger ripples or weighting factor designs are not easily solved. In this paper, a direct current controller that uses an extended high-gain state observer is proposed. The integral controller is removed from the system by using a disturbance estimation technique, which improves the system's performance with a variety of loads. A direct current controller without weighting factors is proposed as the inner controller. Unlike existing direct control methods, all phase currents are considered equally in the controller, which ensures a high current control quality. The simulation and experimental results verify that the proposed method performs well both in steady and transient states. [ABSTRACT FROM AUTHOR]

This paper presents an efficient direct-model predictive control (EDMPC) technique for surface-mounted permanent-magnet synchronous generators (PMSGs) in variable-speed wind energy conversion systems. The proposed control technique is based on directly computing the reference voltage vector (VV) from the demanded currents using a deadbeat (DB) function. Then, a discrete-time integral action (DTIA) is added to this DB function to enhance the robustness of the proposed EDMPC scheme against variations of the machine parameters and to achieve a good steady-state response. The proposed DTIA is simple and easy to implement. Finally, according to the location of this reference VV, two evaluations of the quality function are only required. Accordingly, the proposed EDMPC technique with DTIA overcomes the following drawbacks of the conventional direct-model predictive control (DMPC): high calculation burden, sensitivity to parameters mismatches, and non-zero steady-state error. The performance of the proposed EDMPC technique with DTIA has been experimentally investigated and compared with that of the EDMPC with time delay control approach and with the performance of the convention DMPC using a $\text{14.5}\,\text{kW}$ PMSG. [ABSTRACT FROM AUTHOR]

One of the main drawbacks with the use of finite control set model predictive control (FCS-MPC) in power converters is the variable switching frequency. When not taken into consideration, it can vary randomly depending mainly on the operating point of the system and the sampling time. This will produce a wide distributed voltage and current spectrum, causing audible noise, resonances, and poor steady-state behavior. To address this issue, a new algorithm, based on the control of the switching period within the cost function, is proposed in this paper. The algorithm shows to be very effective in achieving a regular commutation pattern, similar to pulse width modulation (PWM) techniques, which is evidenced even by similarities in the sideband harmonics generated in the voltage spectrum. The algorithm is easy to design and implement, demanding very low computation power, and enables a combination of the advantages of FCS-MPC with the benefits of a PWM-like power quality. Simulations and experimental results are presented to validate the proposed method, which are compared to previously reported FCS-MPC techniques dealing with the same challenge. [ABSTRACT FROM PUBLISHER]

This paper presents a new multilevel converter topology based on a variable or multilevel dc-link stage. This stage is shared by all inverter output phases, thus increasing the number of output voltage levels while reducing the overall number of active devices compared to traditional topologies; therefore, it is called a reduced multilevel converter (RMC). The converter is not capable of reducing the blocking voltage of the devices; hence, unlike other multilevel converters aimed at medium-voltage applications, this converter is interesting for low-voltage- and high-power-quality-demanding applications such as photovoltaic inverters, wind energy conversion systems, and uninterruptible power supplies. The main novelty behind the proposed concept is the basic dc cell used to generate the variable dc-link voltage, which includes a controlled path through the floating capacitors to provide the necessary degree of control to enable a shared multilevel dc link for all the output phases of the converter. The dc cells are connected in a multicell structure to increase the number of levels of the converter. A five-level version of the RMC topology is briefly compared to other five-level converters such as the five-level active neutral-point-clamped converter and the five-level flying capacitor converter. This paper presents the structure of the new topology with its operating principle, switching states, main characteristics, and experimental validation using finite-control-set model-predictive control. [ABSTRACT FROM PUBLISHER]

Finite control set-model predictive control (FCS-MPC) is an interesting alternative for the control of drive systems. However, FCS-MPC requires a large amount of calculation, because it uses all feasible voltage vectors of a power converter for prediction and evaluation. This is an obstacle for its application when the number of voltage vectors of power converter is increased. The computational burden is more challenging when the control objectives are increased. At the same time, matrix converter is an attractive alternative to conventional back-to-back converters with dc link. However, implementation of FCS-MPC for a matrix converter is computationally expensive due to the 27 feasible voltage vectors of the matrix converter. In this paper, a Lookup table is used to reduce the candidate voltage vectors that make the FCS-MPC computationally efficient for matrix converter-fed permanent-magnet synchronous motors. This approach is implemented experimentally and is compared with the conventional approach to evaluate its performance. [ABSTRACT FROM PUBLISHER]

Direct model predictive control (DMPC) is a promising alternative for power electronics and electric drives. It takes the switching nonlinearity of the power converters and system constraints into consideration, without using an extra modulator. However, its one-switching-vector-per-control-interval character leads to big ripples of the control variables. Therefore, with a similar sampling frequency, its steady-state performance is not satisfying. In this paper, we propose a multiple-vector direct model predictive power control (MV-DMPPC) concept for the grid-side power converter control of a back-to-back converter permanent-magnet synchronous generator wind turbine system, using a fully field programmable gate array based solution. The proposed control scheme is compared with the classical DMPPC and two recently reported DMPPC scheme with duty cycle optimizations. Both simulation and experimental tests validate that the control performances are evidently improved with the proposed MV-DMPPC solution. [ABSTRACT FROM AUTHOR]