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This paper proposes a sliding fractional order (SFO) control strategy to provide robustness feature for integrating a multilevel converter into power grid under the system parameter uncertainties, nonlinear load alterations and grid voltage sag. All dynamics achieved from the input capacitors and output inductances of the multilevel converter are utilized to design the proposed sliding fractional surfaces (SFSs) such that a robust operation of the grid-tied converter-based system is achieved. Then, a SFS-based Lyapunov function is brought forward to assess the proposed controller stability. A thorough analysis of the Lyapunov function is carried out for distinguishing suitable boundaries of the controller coefficients when the error components of the system state variables are changed, accordingly. Using the derivative of Lyapunov function and SFS, a comprehensive evaluation is executed to detail regulation procedure for the robustness and fractional PI controller coefficients. Finally, a closed-loop system using the converter current dynamics aims to discern the differences between different values of fractional order (FO). Experimental tests using dSPACE-1202 along with MATLAB/Simulink simulations are employed to verify the effectiveness of the proposed control technique for providing proper harmonic compensation, enhanced power quality, unity power factor, voltage sag tolerance, and very low THD grid current.

Despite being cost-effective, seven-level Modified Packed U-Cell (MPUC7) active rectifier tends to be unstable due to unequal dc-links. Thus, a multiobjective controller is required to stabilize voltages and currents besides preserving efficiency and power quality. While conventional finite-set model predictive control (FSMPC) can deal with the multiobjective problem, it cannot assure the system stability, and its weighing factors tuning significantly becomes tiresome as the number of objectives increases. This article presents a low-frequency adaptive FSMPC (AMPC) stabilized based on Lyapunov stability theory to overcome the design problems of FSMPC. AMPC handles four control objectives and a decoupled stability objective. The control objectives assure the standard performance of MPUC7 in terms of switching losses, d v /d t , THD, and capacitors ripple. The stability objective guarantees the rectifier reliability under unstable conditions. The weighting factors in AMPC are floating to tackle the tuning challenges where a radial basis function neural network controller (RBFC) adjusts their variations. RBFC is trained by a novel self-training method including particle swarm optimization (PSO) algorithm and some mathematical analyses without using any training data. Experimental and simulation tests also evaluate AMPC in different conditions to confirm its reliability in fulfilling the desired objectives.

This article proposes a passivity method synthesized by an adaptive neuro fuzzy inference system (ANFIS) to control a grid-tied nine-level packed E-cell (PEC9) inverter. PEC9 is an optimized components count of single-phase, single-dc-source, compact multilevel converter with an appealing feature of dc capacitors horizontal extension. Indeed, PEC9 forms a single auxiliary dc-bus to actively balance its voltages so as grid-tied controller would not be charge of capacitors voltages balancing. Hence, the proposed intelligent-based passivity control (IPC) is designed using only the dynamical model of the PEC9 inverter current. The zero dynamics of state variable errors are obtained and a damping coefficient matrix is presented to theoretically analyze the convergence rate of PEC9 inverter currents under the proposed control functions. In addition, various operating margins of damping coefficients are inquired. So, using the margins, a trained ANFIS as an online estimator tracks the damping injections. It precisely regulates the damping coefficients in unstable conditions; thus, the excellent PEC9 inverter operation is guaranteed. Experiments and simulations validate high reliable performance of the proposed IPC technique under various grid-tied operational conditions.

Training the weighting factors of model predictive control in multiobjective problems is a time consuming and sophisticated process. In this article, conventional model predictive control (CMPC) has been developed as supervised learning model predictive control (SLMPC) to cancel common-mode voltage (CMV) in a three-phase neutral-point-clamped (NPC) inverter, while other control objectives are desirably tracked. SLMPC is accurately and quickly trained through the artificial bee colony (ABC) algorithm to optimize the controller weighting factors. Using the optimized weighting factors, transient response is minimized and CMV is surpassed. After training the weighting factors, SLMPC containing the optimized waiting factors is applied to the three-phase NPC inverter without considering the ABC algorithm in the control loop. By applying the optimized weighting factors to the cost function, SLMPC has been evaluated under several experimental and simulation tests to show that desired control objectives, particularly CMV suppression, have been attained. The proposed training process can be generalized and used for MPC cost functions with more control objectives to obtain the best possible performance.

In this article, a trained artificial neural network (ANN) input–output feedback linearization (IOFL) control strategy is proposed for a grid-connected nine-level packed E-cell (PEC9) converter under various operating variations. For the first time, a second-order dynamic model in d–q reference frame is developed for PEC9 converter. This model enforces the converter to employ IOFL-based proportional–resonance compensators for accurately contributing to current tracking enhancement, mitigation at the current ripple, and consequently, the capacitors dc voltages ripple. As another contribution, the current tracking ability of the proposed controller is much more promoted by decoupling the d–q dynamic components. Indeed, the effect of each proposed control component is fortified through decoupling feedback coefficients. In addition, as the third contribution, ANN as the complementary controller adapts the proposed IOFL-based controller coefficients to improve efficiency and stability of the whole control loop system, including the PEC9 capacitor voltages in unstable operation of load, grid, and dc source as well as in the presence of parameters mismatch and disturbances. To support the aforementioned contributions with more details, the closed-loop description and the dynamic model of the proposed controller-based PEC9 converter are utilized to present several stability evaluation processes in both time and frequency domains. This assessment process is accurately executed to confirm the stable performance of PEC9 when the errors of the PEC9 converter currents are changed as well as the decoupling feedback coefficients are varied. Finally, comparative dSPACE setup-based experimental and simulation results are attained to further verify the validity of the proposed control strategy under various operating conditions.

In this article, a back-stepping method (BSM) in a–b–c reference is presented to establish the stable operating conditions for modular multilevel converter (MMC). The designed BSM utilizes arm currents, sum of submodule capacitors voltages and MMC input energy as the main variables to form the energy functions. The proposed BSM is designed by well-known dynamic MMC equations to be applicable for both single- and three-phase ones while the control of variables is also guaranteed by BSM. A virtual control input containing input energy error and its dynamics is defined in the second energy function to further enhance the appropriate transient responses of the MMC. The proposed BSM has inherent feature of the circulating current suppression control loops which helps avoiding additional control loops. Moreover, several assessments are presented to show how BSM coefficients contribute to the noticeable decrement in control variables errors of the MMC system. Experimental and simulation results prove an excellent capability of BSM for controlling MMCs compared to the conventional PI linear controller. Moreover, the BSM robustness against the variations of the MMC circuit parameters is validated.

This study proposes a control technique for single-input dual-output three-level dc-dc converter (SIDO-TLC) using feedback (FB) and feedforward (FF) principles. Through the proposed control strategy, SIDO-TLC can smoothly function in both buck and boost operating conditions with a fast dynamic. Major duties of the designed FB control loops are to noticeably decrease the recovery time of transient responses under the load variations and accurately balance the boost capacitors voltages. To effectively decouple the introduced control inputs, an external FF controller is assigned that can also enhance the buck and boost voltage regulations. Furthermore, a step-by-step assessment is contemplated based on the proposed control loops to make an offline adjustment for the FB and FF coefficients. The proposed controller implemented on SIDO-TLC is highly suitable for portable applications, where efficiency, cost, and speed are of important factors. The simulation results and the laboratory test setup of SIDO-TLC using DSP TMS320F28335 are presented to prove the validity of the presented theoretical subjects.

In this paper, an adaptive fuzzy passivity-based control strategy is proposed to provide stable operation for a grid-tied nine-level packed E-Cell (PEC9) converter. Passivity theory is developed in the first step to enable the error dynamics of the PEC9 converter currents to reach a much more effective convergence rate using the proposed damping coefficients. Moreover, various operating margins are achieved for the damping coefficients through PEC9 current errors-based 3D curves. In order to establish online estimation for the damping coefficients, the fuzzy controller and Artificial Neural Network (ANN) are combined. Experimental and simulation results are employed to validate the accuracy of the proposed control technique under load variation, parameter mismatch and DC-link voltage variation.

An accurate reference current detection (RCD) algorithm with the ability of double-frequency oscillation cancellation (DFOC) is designed in this paper to control a nine-level packed E-cell (PEC9) as a single-phase active power filter (SPAPF). The reference current is detected through DFOC-based RCD and subsequently injected by the converter. The detected current contains all unnecessary components and is accurate enough to keep the grid current in sinusoidal form with the THD under the permitted threshold. The proposed PEC9-based SPAPF not only guarantees the power quality at the grid side, but also benefits all advantages of PEC multilevel converter. The effectiveness of the proposed SPAPF is assessed in comparison with conventional one and its performance is investigated via simulation studies by using MATLAB/SIMULINK software.

International audience; The main challenge in hybrid wind-battery systems is the battery cost including investment and replacement. Thus, numerous studies have been conducted on cost minimization. Previous studies often focused on the battery sizing, while the battery performance has also the significant effect on the battery replacement and in turn battery cost. In this paper, a new approach is proposed to improve the battery performance and lifetime. We proposed an extended two-set battery model with new scenarios and formulation to achieve a balance between batteries and managing their power during prediction error. In this model, shallow charge/discharge cycles are eliminated, and batteries experience complete cycles. Furthermore, the battery availability is increased. The simulation results for a case study are presented and the results show the effectiveness of the proposed approach in comparison of conventional models.

In this paper a novel single dc-source switch-capacitor compact multilevel topology is designed based on Packed E-Cell to have the boosting potency for the 11-level operation and to merit as a reliable AC-DC converter for fault tolerant capability. The proposed single-phase compact converter is reduced the active/passive components counts while the output voltage levels are increased which it includes 6 normal power switches and 3 bidirectional switches as well as 2 dc capacitors as the auxiliary dc sources. While the conventional compact converter is incapable of fault tolerant operation, the proposed topology could emerge as a reliable while it has the boosting ability due to its switched-capacitor feature. Moreover, the dc capacitors are actively balanced thanks to various switching states redundancy. The proposed single-phase switched-capacitor converter is validated by theoretical analyses as well as simulation results obtained by Matlab-Simulink where it shows the accurate dc capacitors voltages balancing and prefect 11-level generation in the AC output terminal.

The presented article introduces a versatile multilevel inverter based on Packed E-Cell (PEC) topology. This structure is suitable for conversion of photovoltaic energy generations to supply AC loads and uninterruptible power supplies (UPS). Requiring a reduced number of power switches and capacitors compared to other inverters along its control simplicity are the prominent merits of this converter. Thanks to the horizontally extension of the shunt-capacitors, both of them can be charged or discharged to a quarter if the input source, at the same time. Hence, by applying two isolated input sources and one voltage sensor, the proposed inverter generates 17-levels for the output voltage. Simple level shifted pulse width modulation technique (LS-PWM) is used to control the operation of the proposed inverter. Finally, the accurate performance of the proposed multilevel structure is investigated through MATLAB simulations.

In this paper, a new asymmetric multilevel inverter (MLI) topology proposed to avoid the drawbacks of using numerous DC voltage sources and H-bridge cells in asymmetric MLIs. This structure consists of two modules. The first module is a five-level neutral point clamped (NPC5) and the second module is a nine-level packed E-cell converter (PEC9) containing a few low-cost and low-size devices. These modules are connected to each other, and a hybrid PWM modulation is operated to result in the 41-level asymmetric inverter. The proposed hybrid PWM modulation causes to operate only five low voltage and low power switches at the switching frequency, while the rest of the switches operate at low frequency or at the fundamental frequency, which reduces the size and cost of the proposed 41-level inverter. The presented simulations by MATLAB SIMULINK confirm the suitable performance of the inverter as well as the proposed hybrid modulation method.

This paper presents a grid-integrated multilevel inverter based on Packed E-Cell (PEC) structure for connecting renewable energy sources to the existing power grids. This dual source topology benefits from low number of semiconductor devices, simple robust control strategy, and smooth current of the capacitors. The shunt-capacitors of the converter are charged or discharged simultaneously to a quarter of the input DC source via horizontally extension design of the circuit. Thus, by applying only one voltage sensor and simple phase disposition pulse width modulation approach (PD-PWM), the operation of the inverter to generate 17-levels for the output voltage is ensured. For improving the dynamic performance of the converter, a closed-loop controller is designed and a precise mathematical analysis is presented as well. Accurate performance of the proposed structure is assessed by calculating theoretical analyses and simulating the inverter in MATLAB Environment.

This paper proposes a robust H ∞ vector current control strategy for grid-tied single-phase nine-level Packed ECell (PEC) inverters under grid impedance uncertainty. A multi-input multi-output polytopic model is developed for the grid-tied PEC with the grid impedance uncertainty. By virtue of this novel model, a robust H ∞ vector current control framework is then proposed. The current controller design problem with desired performance specifications is formulated as a convex optimization problem. The main feature of the proposed control approach is that it guarantees robust stability and satisfactory performance against the uncertainty in grid impedance. The effectiveness of the proposed control strategy is evaluated by simulation case studies and experimental results.

This paper focuses on designing an intelligent linearization control strategy for a nine-level packed E-Cell (PEC9) converter in grid-connected mode when the load and the inverter parameters are changed. The linearization controller is constructed based on input-output feedback linearization (IOFL) control strategy through a second-order dynamic model in d-q reference frame developed for PEC9 converter. In order to properly adapt the coefficients of proposed linearization controller in presence of load variations as well as parameter mismatch, an artificial neural network (ANN) tuner based on ABC algorithm and IAE cost function is developed. Several comparative simulation results are presented when the filter inductance mismatch and the current reference variations occur. The results verify the ability and superiority of proposed controller at suitable intelligent tuning of the controller coefficients.

This paper is dealing with designing an advanced Direct Power Control (DPC) technique for a grid-connected nine-level Packed E-Cell (PEC9) inverter through Finite Control Set Model Predictive Control (FCSMPC) and Single-phase Direct-Quadrature (s-d-q) frame. Generating a nine-level voltage waveform using minimum active and passive components count makes PEC9 a cost-effective compact multilevel converter in single-phase applications. FSMPC symmetrically stabilizes the nine-level voltage waveform and accurately synchronizes the inverter current with the grid voltage by applying direct control to the switching operation of PEC9 inverter. The phase and the amplitude of the reference current in the proposed DPC are adjusted regarding the desired level of active and reactive power through s-d-q frame. In order to address the FCSMPC weighting factors tuning difficulty, some new adaptive functions using the error value of the capacitors voltages and the inverter current are also proposed. The experiments and simulations approve that PEC9 accurately generates the desired amounts of active and reactive power with standard level of THD and dc voltage ripple.

In this paper, the input-output feedback linearization (IOFL) theory is applied to modular multilevel converter (MMC) dynamics to design the initial control strategy. Then, direct Lyapunov method is used to complete the control strategy by attaining several effective low pass filters (LPFs). In the process of achieving LPFs, global stability of the considered MMC-based high voltage dc (HVDC) system is guaranteed through the d and q components of both MMC output and circulating currents dynamics. To this end, the errors of proposed control functions with suitable Lyapunov coefficients are used to shape the energy function. Simulation results in MATLAB/SIMULINK environment are provided to verify effectiveness of the proposed control strategy at reaching a good dynamic response for a MMC-based HVDC system under fault condition.

Compact Multilevel Converters (CMCs) are type of converter topology where both DC sources and AC loads are clamped by active switches and the load current directly passes though DC sources. The H-bridge has been emerged as the first generation of CMCs, but later H-bridge has been developed as Packed U-Cell (PUC) using auxiliary DC capacitors instead of extra DC sources and optimizing number of components. Recently, an advanced CMC based on the PUC has been introduced so-called as Packed E-Cell (PEC) which is further optimized compared to PUC topology. The main challenge in CMCs including PEC is to balance the auxiliary DC capacitors in a low switching frequency technique. In this paper, DC capacitor voltage balancing of PEC is investigated at a low switching frequency operation using Selective Harmonic Mitigation (SHM) modulation technique. Some theoretical and simulation analyses have been performed to evaluate the performance of PEC under low switching frequency operation.

This paper proposes a control strategy for a nine-level Packed E-Cell (PEC9) converter to act as Static Synchronous Compensators (STATCOMs). The controller is aimed to support grid stability through controlling the injection of PEC9 active and reactive power. The controller is designed in such way which second-order responses for the errors of PEC9 power can be reached. By analyzing the responses, a tuning process is presented for the controller coefficients as well. Simulation results in MATLAB/SIMULINK verifies the ability of proposed PEC9-based STATCOM.

Controlling active and reactive powers in single-phase grid-connected inverters is matter of issue. This paper proposes an intelligent controller using Radial Basis Function (RBF) artificial neural network in a single-phase Direct Quadrant (DQ) frame to control active and reactive powers generated by nine-level Packed E-Cell (PEC9) inverter. Because of using single DC source, single DC link and less number of power switches, PEC9 is much interesting for grid-tied applications. In the proposed RBF-based control loop, active and reactive powers are separately controlled by using single-phase DQ transform. Since the grid current is converted to DC form, transient and steady-state errors can be suppressed remarkably. Simulation tests performed by MATLAB software show that the proposed DQRBF control loop desirably tracks active and reactive current references without significant transient response under different dynamic modes. The results also illustrate low THD, minimum capacitor voltage ripple and unity power factor.

Multilevel converters can be considered as a worthy alternative for microgrid applications because of their abilities at reaching more active and reactive power generation as well as more suitable power quality enhancement. In this paper, two parallel 9-level Packed E-Cell (PEC9) inverters are utilized to form a grid-connected microgrid with LCL filter. Based on the microgrid specifications, the dynamics of the PEC9 output currents and C filter voltages in d-q reference frame are incorporated in a feedback-feedforward control strategy to manage the power sharing of the inverters for grid stability and unity power factor. The proposed control technique is evaluated through the PEC9 output current-based transfer functions to achieve effective control coefficients. The microgrid system is assessed by Matlab/Simulink environment under load variations to verify the proposed control strategy abilities.

This paper presents a robust controller based on Lyapunov Control Theory (LCT) and Artificial Neural Network (ANN) for the grid-tied single-phase nine-level Packed E-Cell (PEC9) inverter. The proposed robust controller is designed using nonlinear model of the grid-tied PEC9 in which a proper negative definite function with a Positive Weighting Factor (PWF) obtained by LCT guarantees the designed controller to provide globally asymptotically stability for the system in unsteady conditions. An online ANN Estimator (ANNE) is also designed to update the PWF which has the most effect on controller performance. ANNE is also trained through an online optimization loop based on Artificial Bee Colony (ABC) algorithm that reduces the training time dramatically and enhances precision of the trained estimator. Some experimental and simulation tests are accomplished by dSpace-1104 hardware and MATLAB/Simulink software to confirm the high accuracy and fast transient response of the proposed LCT-ANNE in the current reference tracking and obtaining low injected current THD for both steady-state and variable conditions of the grid-tied PEC9.

This paper aims to present a novel control strategy for modular multilevel converters (MMC) based on differential flatness theory, in which instantaneous active and reactive power values are considered as the flat outputs. To this purpose, a mathematical model of the MMC taking into account dynamics of the ac-side current and the dc-side voltage of the converter is derived in a d-q reference frame. Using this model, the flat outputs-based dynamic model of MMC is obtained to reach the initial value of the proposed controller inputs. In order to mitigate the negative effects of the input disturbance, model errors, and system uncertainties on the operating performance of the MMC, the integral-proportional terms of the flat output errors are added to the initial inputs. This can be achieved through defining a control Lyapunov function which can ensure the stability of the MMC under various operating points. Moreover, the small-signal linearization method is applied to the proposed flat output-based model to separately evaluate the variation effects of controller inputs on flat outputs. The proficiency of the proposed method is researched via MATLAB simulation. Simulation results highlight the capability of the proposed controller in both steady-state and transient conditions in maintaining MMC currents and voltages, through managing active and reactive power.

A multi-loop control strategy based on a six-order dynamic model of the modular multilevel converter (MMC) is presented in this paper for the high-voltage direct current (HVDC) applications. For the initial analysis of the operation of MMC, a capability curve based on active and reactive power of the MMC is achieved through a part of the six order dynamic equations. According to the MMC’s control aims, the first loop known as the outer loop is designed based on passivity control theory to force the MMC state variables to follow their reference values. As the second loop with the use of sliding mode control, the central loop should provide appropriate performance for the MMC under variations of the MMC’s parameters. Another main part of the proposed controller is defined for the third inner loop to accomplish the accurate generation of reference values. Also, for a deeper analysis of the MMC’s dc link voltage stability, two phase diagrams of the dc-link voltage are assessed. Matlab/Simulink environment is used to thoroughly validate the ability of the proposed control technique for control of the MMC in HVDC application under both load and MMC’s parameters changes.

This study presents a new function-based modulation control technique for modular multilevel converters (MMCs). The main contribution of this study is the formulation of two new modulation functions for the required switching signals of the MMC's upper and lower sub-modules, respectively. The output and circulating current equations of the converter are employed to attain the arm's currents which are utilised for the proposed modulation functions, which have two important features: (i) it is much less complex compared to the existing control methods of MMC; and (ii) the proposed controller can be regulated properly to deal with parameter variations in a bid to ensure stable and accurate performance. In this controller, the MMC output current magnitude and phase angle required for special active and reactive power sharing can be easily applied to the modulation functions. Also, the equivalent capacitors of upper and lower sub-modules are discussed based on the proposed modulation functions. Finally, simulations are performed in Matlab/Simulink environment to evaluate the performance of the proposed control technique in both the dynamic conditions of load as well as varying parameters.

This manuscript introduces a novel Maximum Power Point Tracking (MPPT) technique based on Artificial Neural Network (ANN) to inject harvested electrical power from PV panels to a three-phase stand-alone load using nine-level Packed E-Cell (PEC9) inverter. Instead of using three MPPT algorithms and three duty cycle controllers, the proposed ANN-MPPT technique proposes a single controller to extract the Maximum Power (MP) of three PV panels connected to the three-phase stand-alone PEC9 inverter. PEC9 is a promising multilevel inverters topology which uses least semiconductor switches, capacitors and a single DC source to generate a nine-level quasi-sinusoidal voltage waveform. The proposed three-phase PEC9 inverter control loop has been simulated by MATLAB software where the results show proper power quality, low Common Mode Voltage (CMV) and balanced capacitors voltage with minimum ripple.

In this paper, a modified Level-Shifted PWM technique is integrated to an active capacitor voltage balancing method to apply for the recent introduced compact single-phase multilevel converter so-called as Packed E-Cell (PEC9) topology. PEC9 is composed of a single main DC source, single auxiliary DC link including two connected capacitors in series as well as six power switch and one back-to-back switch forms bidirectional switch which nine level voltage waveforms is achievable at the output AC terminal. PEC9 benefits the advantages such as reduced component, simultaneous charging and discharging capacitors with redundant states led to have an active capacitors voltage balancing algorithm. The modified Level-Shifted PWM is integrated with active capacitor voltage balancing technique to regulate the capacitor voltage to one quarter of DC input voltage so as PEC generates nine-level voltage waveform. According to the proposed modified Level-Shifted PWM, the appropriate switching states from the redundant states are selected in the specified level which guarantees balancing PEC9 DC capacitors. The proposed modulation technique has been tested on PEC9 using Matlab/Simulink and simulation results validate its excellent performance in active DC capacitor voltage balancing.

This article introduces an Optimized SHE-Pulse Width and Amplitude Modulation (OSHE-PWAM) for single-DC source, single-phase nine-level Packed E-Cell (PEC9) to suppress maximum harmonic while switching frequency is minimized. PEC9 is a developed compact multilevel inverter based on the horizontal extension of capacitors to provide single auxiliary DC-bus and effective charging and discharging states for active capacitor voltage balancing. Based on the proposed OSHE, both switching angles and DC input voltage amplitude are considered as variable in the conventional SHE equations and new equations are developed to deal with maximum harmonic elimination. On the other hand, OSHE also handles capacitor voltage balancing by defining a symmetrical preprogramed output voltage waveform for establishing SHE equations. Simulation results are attained by Matlab-Simulink and confirm the excellent operation of the OSHE-PWM obtaining maximum harmonic elimination and achieving capacitor voltage balancing in PEC9 inverter while the switching frequency is minimized.

A proportional-resonance (PR) controller along with virtual admittance compensator (VAC) is proposed in this paper for a grid-connected nine-level Packed E-Cell (PEC9) to enable zero steady state and transient errors for the controlled state variables. In order to present further detailed assessments, the closed-loop system of the proposed control strategy is attained to analyze the effects of the coefficients of PR controller as well as the VAC coefficient under various operating conditions. The grid-connected PEC9 is simulated by Matlab/Simulink environment under load variation to verify the validity of the proposed control strategy.

In this paper, an improved Adaptive Neural Fuzzy Inference System (ANFIS) based controller has been designed to regulate the capacitor voltage and load current of Seven-Level Packed U-Cell (PUC7) inverter. PUC7 is an affordable topology due to the least power switches and DC sources; but, it suffers from unstable adjusting capacitor voltage level. Proportional Integral (PI) as a simple linear control method causes overshoots and undershoots in transient response and conducts the system to unstable mode when some uncertainties are existed in the load. However, the proposed ANFIS control method regulates the load current and balances the capacitor voltage without any overshoot or undershoot and transient response even in presence of nonlinear loads. Simulation results of stand-alone mode of operation of PUC7 obtained by MATLAB software also confirm usability of ANFIS control loop to achieve unity power factor, minimum Total Harmonic Distortion (THD) and minimum capacitor voltage ripple while the PUC7 inverter is connected to an AC dynamic load.

This paper presents a control strategy for a Multi-Terminal MMC-HVDC system to enhance the frequency response of AC grids. Using power sharing of both upper and lower arms of MMC combined with a basic equation of control functions, the proposed upper and lower control functions are extracted. In these proposed control functions, total wasted power in both upper and lower arms along with the power generated by the arm inductances are considered. The proposed control functions are capable of providing accurate performance with fast frequency response for AC grids with the existence of both load variations and DC voltage fluctuations. MATLAB/SIMULINK software is employed to demonstrate the merit of proposed controller.

In this paper, First Order Sliding Mode Control (FOSMC) has been optimally designed for single-phase grid-connected Packed E-Cell (PEC) inverter. PEC is a recent introduced advanced compact inverter topology generates multilevel voltage while capacitors are balanced using the redundant switching states. Therefore, the capacitor voltage balancing is no longer required to be assumed in the grid-connected controller. According to the proposed FOSMC, the sign function is replaced by saturation function to mitigate the chattering phenomenon and improve the controller performance. Afterwards, FOSMC weighting factors are optimized by Artificial Bee Colony (ABC) algorithm to compensate the saturation function error. The proposed OFOSMC has been evaluated by simulation and experimental analyses under both steady and variable conditions to investigate its performance in controlling grid-connected PEC inverter. The obtained results show least tracking error and fast transient response where low THD and capacitor voltage ripple are obtained.

In this paper, a finite set model predictive control (FSMPC) with low switching frequency is designed for a modified seven-level Packed U-Cell (PUC) converter to work in rectifier mode of operation. In the proposed FSMPC, a cost function is derived by the use of the modified rectifier dynamic equations to choose a switching vector with the minimum cost for each sampling time so as the switching frequency is minimized. The single control loop of proposed FSMPC consisted of suitable controllable parameters are achieved by the accurate mathematical-based analyses of proposed 3D curves. The 3D curves are driven by the use of a proportional cost function as well as the dynamic behaviors of rectifier. The developed MPC scheme has been tested on the modified seven-level PUC rectifier by simulation and experimental analyses to validate the sinusoidal grid current with very low THD, unity power factor, and output DC voltages with negligible fluctuations.

This paper synthesizes input-output feedback linearization (IOFL) and sliding mode controller (SMC) for a hybrid AC/DC microgrid system under both load variations and parameter uncertainties. The controller is indeed aimed to provide an optimal coordinated performance strategy for power electronic converters in both grid-connected and islanding operating conditions for the power management of the hybrid microgrid. The operation of two DC/AC converters in the hybrid microgrid is enriched through the dynamic model completion and the control ability promotion in the islanding mode. The initial control functions for power electronic converters are firstly shaped based on applying the IOFL basics to a comprehensive dynamic model. To reach robustness feature for the controller, the sliding surfaces based on the current errors of the power converters are presented. Then, based on the DC-link voltage transfer functions, it is comprehensively evaluated how much the compensators and sliding coefficients can impact the stability margin and tracking capability of the proposed control functions. In addition, to further investigation, several cost functions are attained through the second-order responses of DC-link voltage to obtain optimal values for the controller coefficients. Simulation results in the MATLAB/SIMULINK environment are employed to show the validity of the proposed control technique under load variations, parameters uncertainty and controller coefficients alteration. Also, some comparative simulation results are attained for verifying the superiority of the proposed control technique.

This paper presents a coordinated control strategy based on direct Lyapunov theory to handle the consistency of AC grids in a multi-terminal (MT) modular multilevel converter (MMC)-HVDC systems during varying both loads and DC link voltage. As the first contribution, a set of dynamic equations is proposed based on separating the dynamics of MMCs upper and lower arms state variables. The dynamics consists of only their related upper/lower arms state variables leading to more effective components for the steady state terms of proposed control technique. To develop the dynamic parts of the controller, the global asymptotical stability of MT MMC-HVDC system is assessed by direct Lyapunov method. As another advantage of the separated dynamic equations, the Lyapunov theory is able to exploit very simple decoupled components for the dynamic parts of proposed control functions. Moreover, in order to specify the variation trend of Lyapunov coefficients, further stability analysis contributes to demonstrating the effects of Lyapunov coefficients on the MMCs state variable errors and its dynamic. As another main contribution of this paper, two independent capability curves based on the power injection capability of the MMCs upper and lower arms, are obtained which will be assessed through changing the input and output voltages as well as MMC parameters. Finally, simulation results in MATLAB software are utilized to verify the validity of proposed control strategy.