Dr. Ola Ibrahim
Academic Qualifications:
May 22, 2022 PhD in Control and Automation Engineering.
September 1, 2013 Master's Degree in Electronic Engineering, Department of Control and Automation Engineering.
September 17, 2009 Bachelor's Degree in Electronic Engineering, Department of Control and Automation Engineering.
Contact
- Alaa_Ibrahim@ebla.edu.sy
Experiences:
Academic Experience:
2023 – Present Faculty Member – Department of Informatics and Communications, Faculty of Engineering, Ebla Private University.
2010 – 2013 Part-Time Lecturer – Applied Faculty, University of Latakia.
2010 – 2013 Technical Staff Member – Department of Computer and Automation Engineering, Faculty of Mechanical and Electrical Engineering, University of Latakia.
2010 – 2013 Technical Staff Member – Department of Control and Automation Engineering, Faculty of Electrical and Electronic Engineering, University of Aleppo.
Researches:
Studying of Bi-Directional Inverter Controlled by Classic and Advanced Controllers - Case Study (PWM Rectifier)
The rectifier was controlled using the Voltage Oriented Control (VOC) algorithm, employing three types of controllers within the MATLAB/Simulink environment: the PI controller, the Optimal controller, and the Sliding Mode Controller (SMC). The performance of these controllers was then tested under variations in system parameters and load current changes, comparing their robustness in overcoming these disturbances.
مجلة بحوث جامعة حلب15 - July - 2021
Read More >>Comparison between PI and Hysteresis Controllers of Voltage Oriented Control based Three-Phase PWM Rectifier
Two control algorithms for the rectifier were studied based on the Voltage Oriented Control (VOC) technique. Both algorithms were simulated using PSIM (Power Simulation) software, followed by a comparison of the results obtained from each algorithm.
Latakia Research Journal10 - February - 2019
Read More >>Monitoring and Fault Diagnosis of one-Phase voltage-source inverter using Statical Analysis and Neural Networks
it relies on detecting open-circuit and short-circuit faults in one of the single-phase bridge inverter transistors by extracting the distinctive features associated with each fault, where these features form the training base for the neural network.
مجلة بحوث جامعة حلب11 - April - 2013
Read More >>
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