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Mohamed Abdelrahem (Senior Member, IEEE) was born in Assiut, Egypt, in 1985. He received the B.Sc. (Hons.) and M.Sc. degrees in electrical engineering from Assiut University, Assiut, in 2007 and 2011, respectively, as well as the Ph.D. degree (Hons.) in electrical engineering from the Technical University of Munich (TUM), Munich, Germany, in 2020. Since 2014, he has been teaching power electronics and renewable energy systems at TUM. Furthermore, he has supervised several master theses in the field of control of power electronics, photovoltaic energy systems, and variable-speed wind energy conversion systems. Since 2019, he has been the Head of the Renewable Energy Systems Research Group, Institute for Electrical Drive Systems and Power Electronics (EAL), TUM. Since 2020, he has been an Assistant Professor at Assiut University. His research interests include power electronics, predictive and encoderless control of variable-speed wind generators, photovoltaic energy systems, and energy storage systems. He has received a number of best paper awards from highly prestigious international conferences of the IEEE.
In this paper, a deadbeat predictive control (DBPC) technique for doubly-fed induction generators (DFIGs) in wind turbine applications is proposed. The major features of DBPC scheme are its quick dynamic performance and its fixed switching frequency. However, the basic concept of DBPC is computing the reference voltage for the next sample from the mathematical model of the generator. Therefore, the DBPC is highly sensitive to variations of the parameters of the DFIG. To reduce this sensitivity, a disturbance observer is designed in this paper to improve the robustness of the proposed DBPC scheme. The proposed observer is very simple and easy to be implemented in real-time applications. The proposed DBPC strategy is implemented in the laboratory. Several experiments are performed with and without mismatches in the DFIG parameters. The experimental results proved the superiority of the proposed DBPC strategy over the traditional DBPC technique.
Mohamed Abdelrahem; Christoph Hackl; Ralph Kennel; Jose Rodriguez. Low Sensitivity Predictive Control for Doubly-Fed Induction Generators Based Wind Turbine Applications. Sustainability 2021, 13, 9150 .
AMA StyleMohamed Abdelrahem, Christoph Hackl, Ralph Kennel, Jose Rodriguez. Low Sensitivity Predictive Control for Doubly-Fed Induction Generators Based Wind Turbine Applications. Sustainability. 2021; 13 (16):9150.
Chicago/Turabian StyleMohamed Abdelrahem; Christoph Hackl; Ralph Kennel; Jose Rodriguez. 2021. "Low Sensitivity Predictive Control for Doubly-Fed Induction Generators Based Wind Turbine Applications." Sustainability 13, no. 16: 9150.
Photovoltaic (PV) power systems are integrated with high penetration levels into the grid. This in turn encourages several modifications for grid codes to sustain grid stability and resilience. Recently, constant power management and regulation is a very common approach, which is used to limit the PV power production. Thus, this article proposes dual-mode power generation algorithm for grid-connected PV systems. The developed system considers the two-stage PV configuration for implementation, where the dual-mode power generation technique is executed within the DC–DC conversion (boost) stage. Most of the techniques adopted for dual-mode power operation employ the conventional perturb and observe method, which is known with unsatisfactory performance at fast-changing atmospheric conditions. Considering this issue, this study suggests a modified maximum power point tracker for power extraction. Furthermore, a new adaptive DC-link controller is developed to improve the DC-link voltage profile at different operating conditions. The adaptive DC-link controller is compared with the traditional PI controller for voltage regulation. The inverter control is accomplished using finite-set model predictive control with two control objectives, namely reference current tracking and switching frequency minimization. The overall control methodology is evaluated at different atmospheric and operating conditions using MATLAB/Simulink software.
Mostafa Ahmed; Ibrahim Harbi; Ralph Kennel; Mohamed Abdelrahem. Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller. Arabian Journal for Science and Engineering 2021, 1 -15.
AMA StyleMostafa Ahmed, Ibrahim Harbi, Ralph Kennel, Mohamed Abdelrahem. Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller. Arabian Journal for Science and Engineering. 2021; ():1-15.
Chicago/Turabian StyleMostafa Ahmed; Ibrahim Harbi; Ralph Kennel; Mohamed Abdelrahem. 2021. "Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller." Arabian Journal for Science and Engineering , no. : 1-15.
In this article, a deadbeat predictive control (DB-PC) strategy for permanent-magnet synchronous generators (PMSGs)-based modern wind turbines is proposed. The main advantages of the DB-PC technique are its excellent dynamics and its constant switching frequency. However, the main idea of DB-PC is obtaining the actuation voltage for the next sample from the mathematical model of the generator. Therefore, the DB-PC is highly sensitive to mismatches in the parameters of the PMSG. In order to obviate this problem, a disturbance estimator (extended Kalman filter (EKF)) is employed in this work to enhance the robustness of the proposed DB-PC scheme by estimating the total disturbance due to parameter mismatches and adding it to the calculation of the actuation voltage. Furthermore, the same EKF observe the rotor speed and position of the PMSG, i.e., mechanical sensors are not required. Moreover, the EKF is able to reduce the harmonic distortion in the stator currents of the PMSG. The proposed DB-PC strategy is implemented in the laboratory. The experimental results proved the superiority of the proposed DB-PC strategy over the traditional DB-PC technique.
Mohamed Abdelrahem; Christoph Hackl; Ralph Kennel. Robust Predictive Control Scheme for Permanent-Magnet Synchronous Generators Based Modern Wind Turbines. Electronics 2021, 10, 1596 .
AMA StyleMohamed Abdelrahem, Christoph Hackl, Ralph Kennel. Robust Predictive Control Scheme for Permanent-Magnet Synchronous Generators Based Modern Wind Turbines. Electronics. 2021; 10 (13):1596.
Chicago/Turabian StyleMohamed Abdelrahem; Christoph Hackl; Ralph Kennel. 2021. "Robust Predictive Control Scheme for Permanent-Magnet Synchronous Generators Based Modern Wind Turbines." Electronics 10, no. 13: 1596.
Voltage source Multilevel Inverters (MLIs) are vital components for medium voltage and high-power applications due to their advantages like modularity and better power quality. However, the number of components used is significant. In this paper, an improved asymmetrical multilevel inverter topology is proposed producing 17-levels output voltage utilizing two dc sources. The circuit is developed to reduce the number of isolated dc-sources used without reducing output levels. The circuit utilizes six two-quadrant switches, three four-quadrant switches and four capacitors. The capacitors are self-balancing and do not require extra attention, i.e. the control system is simple for the proposed MLI. Detailed analysis of the topology under linear and non-linear loading conditions is carried out. Comparison with other similar topologies shows that the proposed topology is superior in device count, power quality, Total Standing Voltage (TSV), and cost factor. The performance of the topology is validated for different load conditions through MATLAB/Simulink environment and the prototype developed in the laboratory. Furthermore, thermal analysis of the circuit is done, and the losses are calculated via PLECS software. The topology offers a total harmonic distortion (THD) of 4.79% in the output voltage, with all the lower order harmonics being less than 5% complying with the IEEE standards.
M. Saad Bin Arif; Uvais Mustafa; Shahrin Bin Md Ayob; Jose Rodriguez; Abdul Nadeem; Mohamed Abdelrahem. Asymmetrical 17-Level Inverter Topology With Reduced Total Standing Voltage and Device Count. IEEE Access 2021, 9, 69710 -69723.
AMA StyleM. Saad Bin Arif, Uvais Mustafa, Shahrin Bin Md Ayob, Jose Rodriguez, Abdul Nadeem, Mohamed Abdelrahem. Asymmetrical 17-Level Inverter Topology With Reduced Total Standing Voltage and Device Count. IEEE Access. 2021; 9 ():69710-69723.
Chicago/Turabian StyleM. Saad Bin Arif; Uvais Mustafa; Shahrin Bin Md Ayob; Jose Rodriguez; Abdul Nadeem; Mohamed Abdelrahem. 2021. "Asymmetrical 17-Level Inverter Topology With Reduced Total Standing Voltage and Device Count." IEEE Access 9, no. : 69710-69723.
This article presents a multiple-vector finite-control-set model predictive control (MV-FCS-MPC) scheme with fuzzy logic for permanent-magnet synchronous motors (PMSMs) used in electric drive systems. The proposed technique is based on discrete space vector modulation (DSVM). The converter’s real voltage vectors are utilized along with new virtual voltage vectors to form switching sequences for each sampling period in order to improve the steady-state performance. Furthermore, to obtain the reference voltage vector (VV) directly from the reference current and to reduce the calculation load of the proposed MV-FCS-MPC technique, a deadbeat function (DB) is added. Subsequently, the best real or virtual voltage vector to be applied in the next sampling instant is selected based on a certain cost function. Moreover, a fuzzy logic controller is employed in the outer loop for controlling the speed of the rotor. Accordingly, the dynamic response of the speed is improved and the difficulty of the proportional-integral (PI) controller tuning is avoided. The response of the suggested technique is verified by simulation results and compared with that of the conventional FCS-MPC.
Ibrahim Bouguenna; Ahmed Tahour; Ralph Kennel; Mohamed Abdelrahem. Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems. Energies 2021, 14, 1727 .
AMA StyleIbrahim Bouguenna, Ahmed Tahour, Ralph Kennel, Mohamed Abdelrahem. Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems. Energies. 2021; 14 (6):1727.
Chicago/Turabian StyleIbrahim Bouguenna; Ahmed Tahour; Ralph Kennel; Mohamed Abdelrahem. 2021. "Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems." Energies 14, no. 6: 1727.
Sensorless strategies become very popular in modern control techniques because they increase the system reliability. Besides, they can be used as back-up control in case of sensor failure. In this paper, a DC-link sensorless control approach is developed, which is suited for grid-connected PV systems. The studied system is a two-stage PV scheme, where the DC–DC stage (boost converter) is controlled using an adaptive step-size perturb and observe (P&O) method. Further, the inverter control is accomplished by voltage oriented control (VOC). Generally, the VOC is implemented with two cascaded control loops, namely an outer voltage loop and an inner current loop. However, in this work, the outer loop is avoided and the reference current is generated using a losses model for the system. The losses model accounts for the most significant losses in the PV system. Moreover, particle swarm optimization (PSO) is utilized to compensate for the unmodeled losses. The PSO is executed offline for the purpose of calculation burden reduction. The proposed approach simplifies the cascaded VOC strategy and eliminates the DC-link voltage sensor, which in turn decreases the cost of the system. Finally, the proposed technique is compared with the conventional one at different atmospheric conditions and validated using MATLAB simulation results.
Mostafa Ahmed; Mohamed Abdelrahem; Ahmed Farhan; Ibrahim Harbi; Ralph Kennel. DC-link sensorless control strategy for grid-connected PV systems. Electrical Engineering 2021, 1 -11.
AMA StyleMostafa Ahmed, Mohamed Abdelrahem, Ahmed Farhan, Ibrahim Harbi, Ralph Kennel. DC-link sensorless control strategy for grid-connected PV systems. Electrical Engineering. 2021; ():1-11.
Chicago/Turabian StyleMostafa Ahmed; Mohamed Abdelrahem; Ahmed Farhan; Ibrahim Harbi; Ralph Kennel. 2021. "DC-link sensorless control strategy for grid-connected PV systems." Electrical Engineering , no. : 1-11.
In this article, a modified control structure for a single-stage three phase grid-connected photovoltaic (PV) system is presented. In the proposed system, the maximum power point tracking (MPPT) function is developed using a new adaptive model-based technique, in which the maximum power point (MPP) voltage can be precisely located based on the characteristics of the PV source. By doing so, the drift problem associated with the traditional perturb and observe (P&O) technique can be easily solved. Moreover, the inverter control is accomplished using a predictive dead-beat function, which directly estimates the required reference voltages from the commanded reference currents. Then, the reference voltages are applied to a space vector pulse width modulator (SVPWM) for switching state generation. Furthermore, the proposed inverter control avoids the conventional and known cascaded loop structure of the voltage oriented control (VOC) method by elimination of the outer PI controller, and hence the overall control strategy is simplified. The proposed system is compared with different MPPT techniques, including the conventional P&O method and other techniques intended for drift avoidance. The evaluation of the suggested control methodology depends on various radiation profiles created in MATLAB. The proposed technique succeeds at capturing the maximum available power from the PV source with no drift in comparison with other methods.
Mostafa Ahmed; Mohamed Abdelrahem; Ibrahim Harbi; Ralph Kennel. An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems. Energies 2020, 13, 6656 .
AMA StyleMostafa Ahmed, Mohamed Abdelrahem, Ibrahim Harbi, Ralph Kennel. An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems. Energies. 2020; 13 (24):6656.
Chicago/Turabian StyleMostafa Ahmed; Mohamed Abdelrahem; Ibrahim Harbi; Ralph Kennel. 2020. "An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems." Energies 13, no. 24: 6656.
Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) without mechanical sensors, i.e., without incremental encoders or speed transducers. The concept of of the developed LPS-MRAO is obtained from the finite-set model predictive control (FS-MPC). In the proposed LPS-MRAO, an algorithm is presented in order to give a constant number of angles for the rotor position of the DFIG. By using these angles, a certain number of rotor currents can be predicted. Then, a new quality function is defined to find the best angle of the rotor. In the proposed LPS-MRAO, there are not any gains to tune like the classical MRAO, where a proportional-integral is used and must be tuned. Finally, the proposed LPS-MRAO and classical one are experimentally implemented in the laboratory and compared at various operation scenarios and under mismatches in the parameters of the DFIG. The experimental results illustrated that the estimation performance and robustness of the proposed LPS-MRAO are better than those of the classical one.
Mohamed Abdelrahem; Christoph M. Hackl; Ralph Kennel. Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors. Machines 2020, 8, 72 .
AMA StyleMohamed Abdelrahem, Christoph M. Hackl, Ralph Kennel. Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors. Machines. 2020; 8 (4):72.
Chicago/Turabian StyleMohamed Abdelrahem; Christoph M. Hackl; Ralph Kennel. 2020. "Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors." Machines 8, no. 4: 72.
This paper proposes a finite control set model predictive control (FCS-MPC) with a reduced computational burden for a single-phase grid-connected modified packed U-cell multilevel inverter (MPUC-MLI) with two control objectives: reference current tracking and switching frequency minimization. The considered competitive topology consists of two units with six active switches and two DC sources in each unit, allowing the generation of 49 levels in the output voltage, which is considered a significant reduction in the active and passive components compared to the conventional and recently developed topologies of multilevel inverters (MLIs). This topology has 49 different switching states, which means that 49 predictions of the future current and 49 calculations of the cost function are required for each evaluation of the conventional FCS-MPC. Accordingly, the computational load is heavy. Thus, this paper presents two reduced-complexity FCS-MPC methods to reduce the calculation burden. The first technique reduces the computational load almost to half by computing the reference voltage and dividing the states of the MLI into two sets. Based on the reference voltage polarity, one set is defined and evaluated to specify the optimal state, which has a minimal cost function. However, in the second proposed method, only three states of the 49 states are evaluated each iteration, achieving a significant reduction in the execution time and superior control performance compared to the conventional FCS-MPC. A mathematical analysis is conducted based on the reference voltage value to locate the three vectors under evaluation. In the second part of the paper, the sensitivity to parameter variations for the proposed simplified FCS-MPC is investigated and tackled by employing an extended Kalman filter (EKF). In addition, noise related to variable measurement is filtered in the proposed system with the EKF. The simulation investigation was performed using MATLAB/Simulink to validate the system under different operating conditions.
Ibrahim Harbi; Mohamed Abdelrahem; Mostafa Ahmed; Ralph Kennel. Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter. Sustainability 2020, 12, 7997 .
AMA StyleIbrahim Harbi, Mohamed Abdelrahem, Mostafa Ahmed, Ralph Kennel. Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter. Sustainability. 2020; 12 (19):7997.
Chicago/Turabian StyleIbrahim Harbi; Mohamed Abdelrahem; Mostafa Ahmed; Ralph Kennel. 2020. "Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter." Sustainability 12, no. 19: 7997.
A two-level voltage source inverter (2L-VSI) when working under over-modulation regulation potentially has low performance, especially during large reference or load changes. To address this problem, a new calculation method is proposed in this work by determining a new reference vector from the boundary of linear modulation zone as a best vector. The reference vector is synthesized by one or two vectors on the boundary line. Therefore, this technique simplifies the calculations to obtain the duty cycles and uses these duty cycles to identify the overmodulation zones. The proposed method is applied to the Modulated Model Predictive Control (MMPC) and the Space Vector Modulation (SVM) respectively in a 2L-VSI. A comprehensive assessment mathematically proves that both methods are in consistent with each other. Simulations and experiments are carried out to show that the proposed methods can reduce the computational burden and implementation complexity and improve the performance of the 2L-VSI in terms of fast dynamic response and smooth transition between the linear-modulation zone and overmodulation zone.
Ali Sarajian; Cristian F. Garcia; Quanxue Guan; Patrick Wheeler; Davood Arab Khaburi; Ralph Kennel; Jose Rodriguez; Mohamed Abdelrahem. Overmodulation Methods for Modulated Model Predictive Control and Space Vector Modulation. IEEE Transactions on Power Electronics 2020, 36, 4549 -4559.
AMA StyleAli Sarajian, Cristian F. Garcia, Quanxue Guan, Patrick Wheeler, Davood Arab Khaburi, Ralph Kennel, Jose Rodriguez, Mohamed Abdelrahem. Overmodulation Methods for Modulated Model Predictive Control and Space Vector Modulation. IEEE Transactions on Power Electronics. 2020; 36 (4):4549-4559.
Chicago/Turabian StyleAli Sarajian; Cristian F. Garcia; Quanxue Guan; Patrick Wheeler; Davood Arab Khaburi; Ralph Kennel; Jose Rodriguez; Mohamed Abdelrahem. 2020. "Overmodulation Methods for Modulated Model Predictive Control and Space Vector Modulation." IEEE Transactions on Power Electronics 36, no. 4: 4549-4559.
In micro-grid systems, wind turbines are essential power generation sources. The direct-driven surface-mounted permanent-magnet synchronous generators (SMPMSGs) in variable-speed wind generation systems (VS-WGSs) are promising due to their high efficiency/power density and the avoidance of using a gearbox, i.e., regular maintenance and noise are averted. Usually, the main goal of the control system for SMPMSGs is to extract the maximum available power from the wind turbine. To do so, the rotor position/speed of the SMPMSG must be known. Those signals are obtained by the help of an incremental encoder or speed transducer. However, the system reliability is remarkably reduced due to the high failure rate of these mechanical sensors. To avoid this problem, this paper presents a model reference adaptive system with finite-set (MRAS-FS) observer for encoderless control of SMPMSGs in VS-WGSs. The motif of the presented MRAS-FS observer is taken from the direct-model predictive control (DMPC) principle, where a certain number of rotor position angles are utilized to estimate the stator flux of the SMPMSG. Subsequently, a new optimization criterion (also called quality or cost function) is formulated to select the best rotor position angle based on minimizing the error between the estimated and reference value of the stator flux. Accordingly, the traditional fixed-gain proportional-integral regulator generally employed in the classical MRAS observers is not needed. The proposed MRAS-FS observer is validated experimentally, and its estimation response has been compared with the conventional MRAS observer under different conditions. In addition to that, the robustness of the MRAS-FS observer is tested at mismatches in the parameters of the SMPMSG.
Mohamed Abdelrahem; Christoph M. Hackl; José Rodríguez; Ralph Kennel. Model Reference Adaptive System with Finite-Set for Encoderless Control of PMSGs in Micro-Grid Systems. Energies 2020, 13, 4844 .
AMA StyleMohamed Abdelrahem, Christoph M. Hackl, José Rodríguez, Ralph Kennel. Model Reference Adaptive System with Finite-Set for Encoderless Control of PMSGs in Micro-Grid Systems. Energies. 2020; 13 (18):4844.
Chicago/Turabian StyleMohamed Abdelrahem; Christoph M. Hackl; José Rodríguez; Ralph Kennel. 2020. "Model Reference Adaptive System with Finite-Set for Encoderless Control of PMSGs in Micro-Grid Systems." Energies 13, no. 18: 4844.
Finite-control-set model predictive control (FCS-MPC) techniques have been widely applied for power electronics and motor drive. Furthermore, the principles of FCS-MPC have been extended to phase locked loop (PLL), which called finite position set PLL (FPS-PLL), for sensorless control of permanent-magnet synchronous generators (PMSGs) in wind turbine applications (WTAs). However, 64 iterations are essential to find the optimal rotor position, i.e high computational burden. In this paper, two computationally-efficient (CE) FPS-PLLs are proposed for encoderless control of PMSGs in WTAs. The first CE-FPS-PLL1 reduces the number of iterations to 36 with slightly better accuracy than the FPS-PLL, while the second (novel) CE-FPS-PLL2 calls for only 24 iterations to find the best rotor position with significantly better accuracy than the FPS-PLL. The performance of the proposed CE-FPS-PLLs have been experimentally investigated and compared with that of the FPS-PLL and classical PLL using a 14.5 kW PMSG. Furthermore, the robustness of the proposed CE-FPS-PLLs is investigated against variations of the PMSG parameters.
Mohamed Abdelrahem; Christoph M. Hackl; Ralph Kennel; Jose Rodriguez. Computationally Efficient Finite-Position-Set-Phase-Locked Loop for Sensorless Control of PMSGs in Wind Turbine Applications. IEEE Transactions on Power Electronics 2020, 36, 3007 -3016.
AMA StyleMohamed Abdelrahem, Christoph M. Hackl, Ralph Kennel, Jose Rodriguez. Computationally Efficient Finite-Position-Set-Phase-Locked Loop for Sensorless Control of PMSGs in Wind Turbine Applications. IEEE Transactions on Power Electronics. 2020; 36 (3):3007-3016.
Chicago/Turabian StyleMohamed Abdelrahem; Christoph M. Hackl; Ralph Kennel; Jose Rodriguez. 2020. "Computationally Efficient Finite-Position-Set-Phase-Locked Loop for Sensorless Control of PMSGs in Wind Turbine Applications." IEEE Transactions on Power Electronics 36, no. 3: 3007-3016.
To gain fast dynamic response, high performance, and good tracking capability, several control strategies have been applied to synchronous reluctance motors (SynRMs). In this paper, a nonlinear advanced strategy of speed predictive control (SPC) based on the finite control set model predictive control (FCS-MPC) is proposed and simulated for nonlinear SynRMs. The SPC overcomes the limitation of the cascaded control structure of the common vector control by employing a novel strategy that considers all the electrical and mechanical variables in one control law through a new cost function to obtain the switching signals for the power converter. The SynRM flux maps are known based on finite element method (FEM) analysis to take into consideration the effect of the nonlinearity of the machine. To clear the proposed strategy features, a functional and qualitative comparison between the proposed SPC, field-oriented control (FOC) with an anti-windup scheme, and current predictive control (CPC) with outer PI speed control loop is presented. For simplicity, particle swarm optimization (PSO) is performed to tune all the unknown parameters of the control strategies. The comparison features include controller design, dynamic and steady-state behaviors. Simulation results are presented to investigate the benefits and limitations of the three control strategies. Finally, the proposed SPC, FOC, and CPC have their own merits, and all methods encounter the requirements of advanced high-performance drives.
Ahmed Farhan; Mohamed Abdelrahem; Christoph M. Hackl; Ralph Kennel; Adel Shaltout; Amr Saleh. Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors. Machines 2020, 8, 44 .
AMA StyleAhmed Farhan, Mohamed Abdelrahem, Christoph M. Hackl, Ralph Kennel, Adel Shaltout, Amr Saleh. Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors. Machines. 2020; 8 (3):44.
Chicago/Turabian StyleAhmed Farhan; Mohamed Abdelrahem; Christoph M. Hackl; Ralph Kennel; Adel Shaltout; Amr Saleh. 2020. "Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors." Machines 8, no. 3: 44.
Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest due to the predicted lack of conventional sources over the coming years. That shortage is not the only concern, as environmental issues add to this concern also. Thus, this study proposes two-stage PV grid connected system, which is supported with extended Kalman filter (EKF) for parameter estimation. In the first stage, maximum power point tracking (MPPT) for the boost converter is accomplished using new MPPT method in which the switching state of the converter is directly generated after the measurement stage, so it is called direct switching MPPT technique. This technique is compared with the conventional finite control set model predictive control (FCS-MPC) method, where the design of the cost function is based on minimizing the error between the reference and the actual current. The reference current is obtained by employing perturb and observe (P&O) method. In the second stage, the two-level inverter is controlled by means of model predictive control (MPC) with reduced computation burden. Further, to overcome the parameter variations, which is a very common problem in MPC applications, an extended Kalman filter is utilized to eliminate the control algorithm’s dependency on the parameters by providing an efficient estimation. After the inverter, an RL filter is inserted to guarantee the quality of the currents injected into the grid. Finally, the system is validated using Matlab under different operating conditions of atmospheric variation and parameter changes.
Mostafa Ahmed; Mohamed Abdelrahem; Ralph Kennel. Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability. Sustainability 2020, 12, 4542 .
AMA StyleMostafa Ahmed, Mohamed Abdelrahem, Ralph Kennel. Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability. Sustainability. 2020; 12 (11):4542.
Chicago/Turabian StyleMostafa Ahmed; Mohamed Abdelrahem; Ralph Kennel. 2020. "Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability." Sustainability 12, no. 11: 4542.
This paper proposes a computationally efficient and robust direct model predictive control (DMPC) technique with enhanced steady-state performance for power converters tied to the electric utility. The discrete space vector modulation (DSVM) method is considered in the design of the suggested DMPC, where virtual voltage vectors (VVs) besides the real ones are utilized for improving the steady-state response of the proposed controller. Furthermore, for averting the high computational burden and making the proposed control technique simple, a deadbeat (DB) function is employed for calculating the reference VV based on the required reference current. Subsequently, a discrete-time integral term is combined with this DB function to enhance the robustness of the suggested DMPC technique against variations of the model parameters. Finally, the best virtual or real VV is chosen by a certain quality function, which will be applied to the power converter in the next sample. The suggested technique is verified by simulation results and its performance is compared with the classical DMPC and voltage-oriented control (VOC).
Mohamed Abdelrahem; José Rodríguez; Ralph Kennel. Improved Direct Model Predictive Control for Grid-Connected Power Converters. Energies 2020, 13, 2597 .
AMA StyleMohamed Abdelrahem, José Rodríguez, Ralph Kennel. Improved Direct Model Predictive Control for Grid-Connected Power Converters. Energies. 2020; 13 (10):2597.
Chicago/Turabian StyleMohamed Abdelrahem; José Rodríguez; Ralph Kennel. 2020. "Improved Direct Model Predictive Control for Grid-Connected Power Converters." Energies 13, no. 10: 2597.
Maximum Power Point Tracking (MPPT) control is an essential part of every photovoltaic (PV) system, in order to overcome any change in ambient environmental conditions and ensure operation at maximum power.. Recently, micro-inverters have gained a lot of attention due to their ability to track the true MPP for each individual PV module, which is considered a powerful solution to overcome the partial shading and power mismatch problems which exist in series-connected panels. Although the LLC resonant converter has high efficiency and high boosting ability, traditional MPPT techniques based on Pulse Width Modulation (PWM) do not work well with it. In this paper, a fixed frequency predictive MPPT technique is presented for the LLC resonant converter to be used as the first-stage in a PV micro-inverter. Using predictive control enhances the tracking efficiency and reduces the steady state oscillation. Operation with fixed switching frequency for the LLC resonant converter improves the total harmonic distortion profile of the system and ease the selection of circuit magnetic component. To demonstrate the effectiveness of the proposed MPPT technique, the system is simulated using MATLAB/Simulink platform. Furthermore, a 150 W hardware prototype is developed and tested. Both simulation and experimental results are consistent and validate the proper operation of the developed system.
Omar Abdel-Rahim; Nehmedo Alamir; Mohamed Abdelrahem; Mohamed Orabi; Ralph Kennel; Mohamed A. Ismeil. A Phase-Shift-Modulated LLC-Resonant Micro-Inverter Based on Fixed Frequency Predictive-MPPT. Energies 2020, 13, 1460 .
AMA StyleOmar Abdel-Rahim, Nehmedo Alamir, Mohamed Abdelrahem, Mohamed Orabi, Ralph Kennel, Mohamed A. Ismeil. A Phase-Shift-Modulated LLC-Resonant Micro-Inverter Based on Fixed Frequency Predictive-MPPT. Energies. 2020; 13 (6):1460.
Chicago/Turabian StyleOmar Abdel-Rahim; Nehmedo Alamir; Mohamed Abdelrahem; Mohamed Orabi; Ralph Kennel; Mohamed A. Ismeil. 2020. "A Phase-Shift-Modulated LLC-Resonant Micro-Inverter Based on Fixed Frequency Predictive-MPPT." Energies 13, no. 6: 1460.
In this paper, a simplified efficient method for sensorless finite set current predictive control (FSCPC) for synchronous reluctance motor (SynRM) based on extended Kalman filter (EKF) is proposed. The proposed FSCPC is based on reducing the computation burden of the conventional FSCPC by using the commanded reference currents to directly calculate the reference voltage vector (RVV). Therefore, the cost function is calculated for only three times and the necessity to test all possible voltage vectors will be avoided. For sensorless control, EKF is composed to estimate the position and speed of the rotor. Whereas the performance of the proposed FSCPC essentially necessitates the full knowledge of SynRM parameters and provides an insufficient response under the parameter mismatch between the controller and the motor, online parameter estimation based on EKF is combined in the proposed control strategy to estimate all parameters of the machine. Furthermore, for simplicity, the parameters of PI speed controller and initial values of EKF covariance matrices are tuned offline using Particle Swarm Optimization (PSO). To demonstrate the feasibility of the proposed control, it is implemented in MATLAB/Simulink and tested under different operating conditions. Simulation results show high robustness and reliability of the proposed drive.
Ahmed Farhan; Mohamed Abdelrahem; Amr Saleh; Adel Shaltout; Ralph Kennel. Simplified Sensorless Current Predictive Control of Synchronous Reluctance Motor Using Online Parameter Estimation. Energies 2020, 13, 492 .
AMA StyleAhmed Farhan, Mohamed Abdelrahem, Amr Saleh, Adel Shaltout, Ralph Kennel. Simplified Sensorless Current Predictive Control of Synchronous Reluctance Motor Using Online Parameter Estimation. Energies. 2020; 13 (2):492.
Chicago/Turabian StyleAhmed Farhan; Mohamed Abdelrahem; Amr Saleh; Adel Shaltout; Ralph Kennel. 2020. "Simplified Sensorless Current Predictive Control of Synchronous Reluctance Motor Using Online Parameter Estimation." Energies 13, no. 2: 492.
Xiaonan Gao; Mohamed Abdelrahem; Christoph M. Hackl; Zhenbin Zhang; Ralph Kennel. Direct Predictive Speed Control With a Sliding Manifold Term for PMSM Drives. IEEE Journal of Emerging and Selected Topics in Power Electronics 2019, 8, 1258 -1267.
AMA StyleXiaonan Gao, Mohamed Abdelrahem, Christoph M. Hackl, Zhenbin Zhang, Ralph Kennel. Direct Predictive Speed Control With a Sliding Manifold Term for PMSM Drives. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2019; 8 (2):1258-1267.
Chicago/Turabian StyleXiaonan Gao; Mohamed Abdelrahem; Christoph M. Hackl; Zhenbin Zhang; Ralph Kennel. 2019. "Direct Predictive Speed Control With a Sliding Manifold Term for PMSM Drives." IEEE Journal of Emerging and Selected Topics in Power Electronics 8, no. 2: 1258-1267.
This paper presents an efficient direct-model predictive control (EDMPC) technique for surface-mounted permanentmagnet synchronous generators (PMSGs) in variable-speed wind energy conversion systems (WECSs). 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): i) High calculation burden, ii) sensitivity to parameters mismatches, and iii) 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 (TDCA) and with the performance of the convention DMPC using a 14:5kW PMSG.
Mohamed Abdelrahem; Christoph Michael Hackl; Ralph Kennel; Jose Rodriguez. Efficient Direct-Model Predictive Control With Discrete-Time Integral Action for PMSGs. IEEE Transactions on Energy Conversion 2018, 34, 1063 -1072.
AMA StyleMohamed Abdelrahem, Christoph Michael Hackl, Ralph Kennel, Jose Rodriguez. Efficient Direct-Model Predictive Control With Discrete-Time Integral Action for PMSGs. IEEE Transactions on Energy Conversion. 2018; 34 (2):1063-1072.
Chicago/Turabian StyleMohamed Abdelrahem; Christoph Michael Hackl; Ralph Kennel; Jose Rodriguez. 2018. "Efficient Direct-Model Predictive Control With Discrete-Time Integral Action for PMSGs." IEEE Transactions on Energy Conversion 34, no. 2: 1063-1072.
Direct power control (DPC) strategy has attracted wide attention due to its advantages of simple structure, quick response, strong robustness, and elimination of current regulation loops/PWM blocks. Unfortunately, under unbalanced grid voltage, the conventional DPC (CDPC) scheme with the conventional definitions of active and reactive power cannot work well. In order to solve this problem, a new definition of the active power instead of the conventional one is proposed, discussed and used in this paper. As a result, good performance of the system is achieved and neither complicated calculation of a power compensation term nor positive/negative sequence extraction of grid voltages/currents are required. Then, a switching table based DPC strategy is designed based on the new definition of active power and conventional definition of reactive power. The corresponding switching table is suitable to achieve constant active power, constant reactive power and sinusoidal grid currents with very low total harmonic distortions (THDs). Simulation results are presented to confirm the theoretical study and the effectiveness of the proposed DPC with the new definition of active power (DPC-NP). The performance of the proposed DPC-NP is compared with that of the CDPC and that of the DPC with a new definition of reactive power (DPC-NQ).
Billel Kahia; Abdelouahab Bouafia; Abdelmadjid Chaoui; Zhenbin Zhang; Mohamed Abdelrahem; Ralph Kennel. A direct power control strategy for three level neutral-point-clamped rectifier under unbalanced grid voltage. Electric Power Systems Research 2018, 161, 103 -113.
AMA StyleBillel Kahia, Abdelouahab Bouafia, Abdelmadjid Chaoui, Zhenbin Zhang, Mohamed Abdelrahem, Ralph Kennel. A direct power control strategy for three level neutral-point-clamped rectifier under unbalanced grid voltage. Electric Power Systems Research. 2018; 161 ():103-113.
Chicago/Turabian StyleBillel Kahia; Abdelouahab Bouafia; Abdelmadjid Chaoui; Zhenbin Zhang; Mohamed Abdelrahem; Ralph Kennel. 2018. "A direct power control strategy for three level neutral-point-clamped rectifier under unbalanced grid voltage." Electric Power Systems Research 161, no. : 103-113.