Zaid H. Al-Tameemi
Al-Furat Al-Awsat Technical University

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A comparative analysis of the tracking angles and fixed angle systems during sunny and cloudy days under Iraqi conditions Talib Sabah Hussein; Kadhim Nasir Fadhil; Zaid H. Al-Tameemi
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp565-570

Abstract

This paper describes design tow systems tracking angles and fixed angle solar panel to improve the performance of solar energy, during the sunny and cloudy days. Depending on the development of the solar tracking system and amount of solar energy captured by the solar panel per day actually, the project is designed with AT 89552 MC depending upon the light falls on (LDR), data will be reading by AT 89552 MC. and changing the direction of a motor in this direction the solar panel will be moving to capture the maximum of solar energy. The tracking angle solar panel has been efficient than a fixed angle. The results show that the tracking angle solar panel has been more efficient than a fixed angle in sunny and cloudy days in morning and afternoon. The tracking angles system generating higher power than the fixed angle system in a morning. The maximum power occurred during the tracking angles system and fixed angle system in the morning, due to drop efficiency of the panels they get heated during the afternoon.
Review of mobile robots obstacle avoidance, localization, motion planning, and wheels Mustafa A. Mhawesh; Zaid H. Al-Tameemi; Omar Muhammed Neda
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp768-776

Abstract

The main objective of this research is to study the obstacle avoidance, Monte Carlo Localization (MCL) method, motion planning in dynamic networks for mobile robots, and mobile robots wheels depending on the previous published researches. The researchers had done their experiments on different mobile robots and had validated them. This research helps the readers to learn how the robot changes its directions to prevent itself from collisions depending on three ultrasonic sensors. Also, they will learn the localization of the mobile robots depending on the recorded data from RHINO and MINERVA robots. In addition to learning the obstacle avoiding and the localization of mobile robots, the readers will learn new planning framework. Furthermore, they will get knowledge in types of mobile robots wheels.