Browsing by Author "Belaroussi, Oussama"

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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.
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
Real-Time Backstepping Control Based MRAS Speed Estimation of an Induction Machine
(Institute of Electrical and Electronics Engineers Inc, 2023) Benakcha, Meryem; Benakcha, Abdelhamid; Benakcha, Younes; Ammar, Abdelkarim; Belaroussi, Oussama
This work presents a real-time evaluation of a sensorless MRAS-backstepping control applied to an induction process (IM). To run the system in safe mode, a backstepping method is first implemented. It guarantees decoupled torque and flux management of the IM without the need for an additional regulator by removing the proportional/integral controller (PI) and decreasing the number of gains that are highly reliant on the temperature-dependent IM parameters. The backstepping control is designed to attain the required speed and flux, and it is ideally suited for regulating an uncertain system that may be affected by external disturbances. Its formulation is based on the application of Lyapunov functions to assure the overall stability of the system. The second section presents a model reference adaptive system (MRAS) to estimate rotor speed and eliminate the sensor, the system's weakest link. Utilizing dSPACE 1104 cards, the suggested control procedure is evaluated. The achieved experimental results indicate that the entire system runs smoothly, with the proposed MRAS-backstepping providing high performance, the system successfully tracking the speed profile under tolerable load, and the system maintaining its dynamic behavior at different speed levels.