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Article
Design and Implementation of a Line Follower Robot Based on Fuzzy Logic controller by Using Microcontroller
تصميم و تنفيذ الروبوت متتبع الخط بالاعتماد على مسيطر المنطق المضبب باستخدام المسيطر الدقيق

Author: Ahmed A. Radhi احمد علي راضي
Journal: Journal of Al-Ma'moon College مجلة كلية المأمون ISSN: 19924453 Year: 2016 Issue: 28 Pages: 288-303
Publisher: AlMamon University College كلية المامون الجامعة

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Abstract

Robot is widely used to help human to do something, especially for difficult or danger ous tasks. The robot requires, some techniques, sensors and controller have been. In this research robot movement is guided by. Fuzzy logic control as intelligent control applied to govern the robot follow line. Infrared sensors are used to sense line as the input variable for the controller. Based on these signals, the controller control the turning angle of forward movement thus making robot move forward and turning at the same time. A fuzzy logic control was selected for its robustness and flexibility.

استخدم الروبوت على نطاق واسع لمساعدة الإنسان على فعل الاشياء، وخاصة بالنسبة للمهمات الصعبة أو الخطرة, الروبوت يتطلب بعض التقنيات، وأجهزة للاستشعار و تطبيق المتحكم . تم في هذا البحث تطبيق المنطق الضبابي للتحكم الذكي في الروبوت متتبع الخط. واستخدمت أجهزة استشعار بالأشعة تحت الحمراء للاستشعار كمدخلات لوحدة التحكم. وبناء على هذه الإشارات، وحدة التحكم و السيطرة عملت على تحويل زاوية الحركة إلى الأمام وبالتالي جعل الروبوت يتحرك إلى الأمام، وتحويل الاتجاه في الوقت نفسه. وقد تم اختيار المنطق الضبابي لمتانة ومرونة عملة.


Article
Identification and Control of Impressed Current Cathodic Protection System

Authors: Bassim N. Abdul Sada --- Ramzy S. Ali --- Khearia A. Mohammed Ali
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2016 Volume: 12 Issue: 2 Pages: 214-220
Publisher: Basrah University جامعة البصرة

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Abstract

In this paper the identification and control for the impressed current cathodic protection (ICCP) system are present. Firstly, an identification model using an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) was implemented. The identification model consists of four inputs which are the aeration flow rates, the temperature, conductivity, and protection current, and one output that represented by the structure-to-electrolyte potential. The used data taken from an experimental CP system model, type impressed current submerged sample pipe carbon steel. Secondly, two control techniques are used. The first control technique use a conventional Proportional-Integral-Derivative (PID) controller, while the second is the fuzzy controller. The PID controller can be applied to control ICCP system and quite easy to implement. But, it required very fine tuning of its parameters based on the desired value. Furthermore, it needed time response more than fuzzy controller to track reference voltage. So the fuzzy controller has a faster and better response.


Article
Design and Implementation of Neuro-Fuzzy Controller Using FPGA for Sun Tracking System

Authors: Ammar A. Aldair --- Adel A. Obed --- Ali F. Halihal
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2016 Volume: 12 Issue: 2 Pages: 123-136
Publisher: Basrah University جامعة البصرة

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Abstract

Nowadays, renewable energy is being used increasingly because of the global warming and destruction of the environment. Therefore, the studies are concentrating on gain of maximum power from this energy such as the solar energy. A sun tracker is device which rotates a photovoltaic (PV) panel to the sun to get the maximum power. Disturbances which are originated by passing the clouds are one of great challenges in design of the controller in addition to the losses power due to energy consumption in the motors and lifetime limitation of the sun tracker. In this paper, the neuro-fuzzy controller has been designed and implemented using Field Programmable Gate Array (FPGA) board for dual axis sun tracker based on optical sensors to orient the PV panel by two linear actuators. The experimental results reveal that proposed controller is more robust than fuzzy logic controller and proportional-integral (PI) controller since it has been trained offline using Matlab tool box to overcome those disturbances. The proposed controller can track the sun trajectory effectively, where the experimental results reveal that dual axis sun tracker power can collect 50.6% more daily power than fixed angle panel. Whilst one axis sun tracker power can collect 39.4 % more daily power than fixed angle panel. Hence, dual axis sun tracker can collect 8 % more daily power than one axis sun tracker.

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