Bashra Kadhim Oleiwi
University of Technology

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Design of fractional order PID controller for AVR system using whale optimization algorithm Layla H. Abood; Bashra Kadhim Oleiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1410-1418

Abstract

In this paper a robust fractional order PID (FOPID) controller is proposed to control the automatic voltage regulator (AVR) system, the tuning of the controller gains are done using whale optimization algorithm (WOA) and integral time absolute error (ITAE) cost function is adopted to achieve an efficient performance. The transient analysis was done and compared with conventional PID in terms of overshoot, settling time, rise time, and peak time to explain the superiority of the proposed controller. Finally, a robustness analysis is done by adding external disturbances to the system and changing the system parameters by ±20% from its original value, the controller overcomes the disturbances signals with less than 0.25 s and faces the changes of the system values and returning the response within (0.7-1) sec and led the system to the desired response efficiently. The numerical simulations showed that the smart WOA offers satisfying results and faster response reflected clearly on the robust and stable performance of the proposed controller in improving the transient analysis of AVR system response.
Human visualization system based intensive contrast improvement of the collected COVID-19 images Bashra Kadhim Oleiwi; Layla H. Abood; Maad Issa Al Tameemi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1502-1508

Abstract

Enhancement and color correction of images play an important role and can be considered as one of the fundamental and basic operations in image analysis for the purpose of speeding up the diagnosis of the medical images. Improving the quality and contrast of the medical image is the basic requirement for clinicians for obtaining an accurate and accurate medical diagnosis. Thus, getting a clear X-ray image reduces the effort and time-wasting. In this study a new idea will be applied for improving image contrast of the collected COVID-19 X-ray images, this idea is based on using Wiener filter, multilevel of histogram equalization (HE) technique with OpenCV library and then using contrast limited adaptive histogram equalization (CLAHE) techniques with OpenCV library. The proposed methodology programmed in MATLAB software and then implemented using Rasperry Pi 3 model B. The size and resolution of images are different as inputted images and this difference succeeded in proving the strength of the proposed idea. The collected X-ray images have undergone experiential evaluations which clearly showed the effective performance of the proposed methodology.