Publications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/13

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Author: search.filters.author.Ammar, Abdelkarim

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    Performance Enhancement of an LADRC Controller Using LDOB-Based Observers for PMSMs in Electric Vehicles: An Experimental Validation
    (Springer Science and Business Media, 2025) Slimani, Amira; Bourek, Amor; Ammar, Abdelkarim; Kakouche, Khoudir; Benrabah, Abdeldjabar; Hattab, Wassila; Ziane, Djamel
    Electric vehicles (EVs) are progressively acknowledged globally for their capacity to mitigate environmental challenges, improve energy efficiency, decrease emissions, and foster sustainable mobility. Efficient speed adjustment of the electric tri-drive system in electric vehicles, commonly employing permanent magnet synchronous motors (PMSMs), is essential for improving system efficiency. This manuscript introduces a novel finite-control-set model predictive current control (FCS-MPC) method, specifically model predictive current control (MPCC) combined with a linear active disturbance rejection controller (LADRC) for speed control. Unlike traditional LADRC based on a linear extended state observer (LESO), the proposed LADRC integrates a linear disturbance observer (LDOB). The LADRC-LDOB enhances precision, improves response speed, eliminates overshoot during speed changes, and offers greater robustness against external disturbances and parametric uncertainties compared to the LESO-LADRC. Furthermore, the LDOB employs a sophisticated metaheuristic technique, the Harris Hawks optimization (HHO) algorithm, to optimize the observer gain. The performance of the proposed controller is numerically simulated in MATLAB/Simulink and experimentally validated on a control system platform based on dSPACE DS1104. The proposed control improves the PMSM control system by eliminating overshoot, demonstrating significant robustness, and effectively managing external disturbances and parametric uncertainties, as both simulation and experimental results show
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    Active Disturbance Rejection Control Based Sensorless Model Predictive Control for PMSM
    (International Information and Engineering Technology Association, 2024) Dahnoun, Ilyes; Bourek, Amor; Ammar, Abdelkarim; Belaroussi, Oussama
    Improving tracking performance in speed controllers for permanent-magnet synchronous motor (PMSM) drive systems is critical due to internal challenges such as parameter variations, model uncertainty, and external disturbances like load changes. This paper proposes a new method that combines sensorless model predictive control (MPC) with active disturbance rejection control (ADRC), employing an extended state observer (ESO) as a key component of the ADRC. Notably, the proposed ADRC-MPC control integrates the advantages of MPC, such as good time response, high robustness against load variation, and a low effect of parameter variation in comparison to conventional control methods like field-oriented control (FOC). The ADRC-MPC reduces torque and flux ripples and also reduces torque and flux irregularities as well as current harmonics, which presents a major drawback in direct torque control (DTC). The proposed control with finite set model predictive control (FS-MPC) eliminates the PWM modulation and the complexity of continuous control set model predictive control (CCS-MPC). In the outer loop, the ADRC-MPC and the ESO present a very good solution. It presents a lower processing requirement than other controllers, especially the fuzzy logic controller (FLC), and also presents a consistent dynamic behavior across the entire operating range, contrary to the PID. The ADRC with ESO presents a promising solution to these challenges. The effectiveness of the proposed method is demonstrated through numerical simulations using MATLAB/Simulink software and experiments on a 3-kW surface-mounted PMSM drive system. both simulation and experimental results under different conditions show the effectiveness of the proposed approach.
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    Developing and implementing the performance of induction motors used in well pumping systems
    (2022) Belaroussi, Oussama; Terki, Amel; Ammar, Abdelkarim; Fedorovich, Kalinin Vyaslav
    Because water extraction from wells accounts for the bulk of energy consumption in irrigation operations globally, the sustainability and profitability of irrigation are strongly reliant on the energy efficiency of the pumping system. A technique that studies and improves the performance of motors used in well pumping systems is reported in this body of research as having been undertaken. In a similar manner, an experimental investigation of the energy efficiency of two modern systems of induction motor control has been carried out. According to the results, proper control performance is critical to achieving improvements in energy and efficiency. Using DTC-SVM for IM, the purpose of this study is to demonstrate a prototype of a pumping system that is powered by solar energy in the presence of changing radiation levels. Real-time MATLAB/Simulink simulations are used in conjunction with a dSpace 1104 board to carry out the hardware implementation
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    Predictive direct torque control with reduced ripples for induction motor drive based on T‐S fuzzy speed controller
    (2019) Ammar, Abdelkarim; Talbi, Billel; Ameid, Tarek; Azzoug, Younes; Kerrache, Abdelaziz
    Finite-state model predictive control (FS-MPC) has been widely used for controlling power converters and electric drives. Predictive torque control strategy (PTC) evaluates flux and torque in a cost function to generate an optimal inverter switching state in a sampling period. However, the existing PTC method relies on a traditional proportional-integral (PI) controller in the external loop for speed regulation. Consequently, the torque reference may not be generated properly, especially when a sudden variation of load or inertia takes place. This paper proposes an enhanced predictive torque control scheme. A Takagi-Sugeno fuzzy logic controller replaces PI in the external loop for speed regulation. Besides, the proposed controller generates a proper torque reference since it plays an important role in cost function design. This improvement ensures accurate tracking and robust control against different uncertainties. The effectiveness of the presented algorithms is investigated by simulation and experimental validation using MATLAB/Simulink with dSpace 1104 real-time interface