Master of Science

Sep 1, 2014 - Sep 26, 2019

M.Sc. of Electrical Engineering /Power and Machines / Control from University of Mosul with a grade good

Bachelor of Science

Nov 1, 2010 - Jun 1, 2013

B.Sc. in Electrical Engineering/Power and Machines

Biomedical Engineering [Biomedical Engineer]

Feb 1, 2020 - Feb 1, 2023

Performing and carrying out, all necessary complex / advanced installation, maintenance and repair of MSF biomedical equipment and ensuring that as few items and equipment’s are out of service at any given time in both Nablus and Sinuni general Hospitals.

Assistant Lecturer [Lecturer]

Apr 2, 2023 - Present

Assistant Lecturer at Northern Technical University for medical engineering instrumentation techniques

Electricity Trainer [Trainer]

Sep 1, 2019 - Jan 1, 2020

Training beneficiaries on connecting wires to circuit breakers, transformers and other components and also assembling, installing, testing, and maintaining electrical or electronic equipment beside that planning layouts and installation of electrical wiring, equipment and fixtures.

Compressed Extended Kalman Filter for Sensorless Control of Asynchronous Motor

Nov 1, 2020

Journal International Journal on Energy Conversion (IRECON)

publisher Prize Worth Prize

DOI 10.15866/irecon.v8i6.19202

Issue 6

Volume 8

The sensorless control applications of Induction Motors (IM) are largely expanding in industrial applications. This paper presents a new and effective sensorless control approach for IM drive based on Compressed Extended Kalman Filter (CEKF). Moreover, the estimations of the rotor flux components and the IM motor speed are implemented through CEKF algorithm. The effectiveness of the proposed control system of IM and estimation algorithm has been verified through simulation work using MATLAB/Simulink at different torque loads. Furthermore, the estimation scheme has been experimentally tested at full load. The comparison between the Extended Kalman Filter (EKF) and the CEKF are carried out and satisfying simulation and experimental results have shown that the CEKF algorithm is very effective in estimating the IM states with lower computational costs, low storage memory and less complexity during implementation compared to the EKF. The sensorless control system has demonstrated good performance at different torque loads conditions.

Read Publication

Flux and Speed Estimation of Induction Motors using Extended Kalman Filter

Aug 7, 2018

Journal International Journal of Computer Applications

publisher Foundation of Computer Science (FCS), NY, USA

DOI 10.5120/ijca2018917586

Issue 7

Volume 181

The application of the field-oriented control strategy to induction motors needs the knowledge of the rotor flux components. On the other hand, in order to enhance the performance of sensorless control of induction motor, the rotor flux and speed of the induction motor should be known. Therefore In this article and based on the fifth order nonlinear model of the induction motor, the rotor flux and speed of induction motor are being estimated simultaneously using the Extended Kalman Filter (EKF) algorithm. Multiple simulation results are being presented that prove the efficacy of the proposed scheme towards flux and speed estimation of induction motor.

Read Publication