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Article
Implementation and Design of Fuzzy Supervisory Controller for Mobile Robot Manipulator

Authors: Ramzy S. Ali رمزي سالم عبي --- Ammar A. Aldair عمار الدير --- Ali K. Almousawi علي الموسوي
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2016 Volume: 16 Issue: 1 Pages: 1-7
Publisher: Basrah University جامعة البصرة

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Abstract

The Mobile Manipulator Robot (MMR) has manyapplications in different aspects of the life, for example,grasping and transporting, mining, military, manufacturing,construction, and others. The benefits of MMR rise in a dangerous place where the human cannot reach such asdisaster areas and dangerous projects sites. In this work, thePID controller is combined with Fuzzy Logic Controller (FLC)to structure the Fuzzy Supervisory Controller (FSC) toovercome the drawbacks of PID controller and to obtain theadvantages of FLC. Two approaches are suggested for thenavigation of Autonomous Mobile Robot (AMR). These are;goal reaching fuzzy control (GRFC) and the obstacle avoidancefuzzy control (OAFC). The hardware implementation of theAMR is performed using AVR ATmega32 microcontroller, twoDC motors, light dependent resistor (LDR) and five Infra Redsensors. While the Laboratory robot arm with somefabrications is used as manipulator's arm with a five degrees-of-freedom. Then a microcontroller is employed to implement theproposed controller for MMR. The designed MMR is tested inreal environments and give a good navigation.


Article
A Chaotic Crow Search Algorithm for High-Dimensional Optimization Problems

Authors: Dunia S. Tahir ديا ستار طاهر --- Ramzy S. Ali رمزي سالم عبي
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2017 Volume: 17 Issue: 1 Pages: 16-25
Publisher: Basrah University جامعة البصرة

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Abstract

Crow Search Algorithm is an innovative metaheuristic optimization algorithm. In this paper, chaotic mapsare combined into Crow Search Algorithm to increase itsglobal optimization. Ten variant chaotic maps are used and theTent map is found as the best choices for high dimensionalproblems. The novel Chaotic Crow Search Algorithm is reliedon the substitution of a random location of search space andthe awareness parameter of crow with chaotic sequences. Theresults show that the chaotic maps are able to enhance theperformance of the Crow Search Algorithm. Also the novelChaotic Crow Search Algorithm outperforms the conventionalCrow Search Algorithm, the first version of Chaotic Crow SearchThe algorithm, Genetic Algorithm, and Particle SwarmOptimization Algorithm from the point of view of the speedconvergence and the function dimensions

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