Items filtered by date: April 2023
Wednesday, 05 April 2023 06:15

Master Thesis Discussion

 Master Thesis Discussion

The master's thesis of the student (GhufranWaleed Abdel Abbas), majoring in Mechatronics and Robotics, from the Control and Systems Engineering Department, was discussed on Wednesday, 8-3-2023. The thesis title is:

‏Sensorless Speed Control of Brushless DC Motor

The discussion committee consisted of:

Asst. Prof. Dr. Abbas Hussein Issa(Chairman)

Asst. Prof. Dr. BasemGhalebMijbel(Member)

Lect. Dr. Huthaifa Khalil Ibrahim (Member)

Asst. Prof. Dr. FarazdaqRafiqYassin(Member and Supervisor) ‎

‏In this work, a brushless DC motor (BLDC) was used. It is commonly used in ceiling fans and electric vehicles due to its smooth operation and lack of routine maintenance. Two algorithms were used. The first algorithm is the Particle Swarm Optimization (PSO) and the second algorithm is the Grey Wolf Optimization (GWO). In addition, speed and position control system was used without the dependency on the Hall sensors, and this was done utilizing two algorithms, namely the Extended Kalman Filter (EKF) and the Particle Filter (PF). ‏In this work, the GWO was superior to PSO and the Classical PI Controller and sensorless PF was superior to EKF.







Wednesday, 05 April 2023 06:09

Master Thesis Discussion

 Master Thesis Discussion

The master's thesis of the student (Reham Sabah Saeed) majoring in Mechatronics and Robotics from the Control and Systems Engineering Department was discussed on Thursday, 2-3-2023. The thesis title is :

An Automatic COVID-19 Detection System Using Deep Learning

The discussion committee consisted of :

Prof. Dr. Mohamed Youssef Hassan (Chairman)

Asst. Prof. Dr. Ammar Ibrahim (Member)

Asst. Prof Dr. Ahmed Raouf(Member)

‎Asst. Prof. Dr. BushraKadhumOliwi(Member and Supervisor)

‎ In this thesis, the proposed models employed deep learning techniques and convolutional neural networks to design and implement an automated diagnosis system for the binary Classification of COVID-19 based on chest x-ray images as a dataset. Several models have been proposed and improved  for better performance and accurate results





Wednesday, 05 April 2023 06:06

Doctoral Dissertation Discussion

 Doctoral Dissertation Discussion

The doctoral dissertation of the student (Muhannad Helal Hamidi) in engineering major was discussed on Thursday, 23-2-2023. The dissertation title is: ‏Development and Research of an Automated Control System of the Adsorption Process to Obtain Hydrogen from Natural Gas Reforming Products The discussion committee consisted of:

Prof. Dr. Mohamed Youssef Hassan (Chairman)

Prof. Dr. Ikhlas Hamid Karam (Member)

Asst. Prof. Dr. Firas Abdel-Razaq(Member)

Asst. Prof. Dr. BushraKadhumOliwi(Member)

Asst. Prof. Dr. LumaIssa Abdel Karim (Member)

Prof. Dr. Omar FarouqLutfy(Member and Supervisor)

Hydrogen is one of the most important products of the global chemical industry. More than 75% of hydrogen is consumed in the production of ammonia and in oil refining, and there is a continuous increase in the consumption of hydrogen in the energy sector. The objective of the thesis is to ensure the maximum degree of hydrogen extraction with a purity of not less than 99.9% by optimizing the automatic control system. Two mathematical models, upper and lower, were developed to control production, and identification was made for the lower model to be as close as possible to the upper model to be ready for work. The optimization problem was demonstrated and solved by using an objective function to increase the degree of hydrogen extraction with a set of restrictions so that the purity is not less than 99.9%.The upper model was placed in a SCADA system and the lower model was placed in a PLC with a PID as an auxiliary controller.In order to evaluate the effectiveness of the control system, a series of simulation experiments were conducted to show that the developed control system handles disturbances in a shorter time than the rest of the control systems currently used in the same field, which increases the degree of hydrogen extraction.