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Article
Novel Optimization Algorithm Inspired by Camel Traveling Behavior

Authors: Mohammed Khalid Ibrahim --- Ramzy Salim Ali
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2016 Volume: 12 Issue: 2 Pages: 167-177
Publisher: Basrah University جامعة البصرة

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Abstract

This article presents a novel optimization algorithm inspired by camel traveling behavior that called Camel algorithm (CA). Camel is one of the extraordinary animals with many distinguish characters that allow it to withstand the severer desert environment. The Camel algorithm used to find the optimal solution for several different benchmark test functions. The results of CA and the results of GA and PSO algorithms are experimentally compared. The results indicate that the promising search ability of camel algorithm is useful, produce good results and outperform the others for different test functions.


Article
COGNITIVE DYNAMIC NEURAL CONTROLLER DESIGN FOR MOBILE ROBOT BASED ON SELF-TUNING ON-LINE OPTIMIZATION ALGORITHM
تصميم مسيطر عصبي حركي مدرك لأنسان ألي مبني على اساس الخوارزمية الأمثلية ذات التنغيم الذاتي وبشكل حي متصل

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Abstract

This paper presents the design of a cognitive dynamic neural controller (CDNC) for the trajectory tracking of non-holonomic wheeled mobile robot based on the dynamic model with self-tuning on-line optimization algorithm. The aim of the proposed controller is to solve the trajectory tracking problem of the mobile robot by finding the optimal torque control action for the two wheels of mobile robot to follow a pre-defined continuous path precisely and quickly. Particle swarm optimization (PSO) used as a fast and stable self-tuning on-line algorithm to compute the optimal parameters for the proposed controller .The robustness and effectiveness of the proposed tuning algorithm are validated by Matlab simulation results in terms of the capability of overcoming the non-representative dynamic disturbances, minimizing tracking error and obtaining the smooth and optimal torque control signals with minimum number of fitness evaluation.

يقدم هذا البحث تصميم منظومة تحكم للسيطرة على مسارالحركة للربوتات ذات العجلتين مقيدة الاتجاه بأستخدام التحكم الديناميكي العصبي المدرك المبني على خوارزمية الامثل استنادا إلى النموذج الديناميكي والخوارزمية الأمثلية ذات التنغيم الذاتي وبشكل حي متصل . ان الهدف من وحدة التحكم المقترحة هو الحصول على منظومة سيطرة ذات ادراك للربوتات المتحركة ذات العجلتين في تتابع مسار محدد مسبقا بسرعة وبدقة. ويتم الحصول على القيم المثلى لعناصر وحدة التحكم على طول المسار باستخدام خوارزمية حشد الجسيمات الأمثلية. من خلال نتائج المحاكاة تم اثبات متانة وكفاءة خوارزمية تنغيم المسيطر المقترح و باستخدام لغة الماتلاب, حيث تم تتبع المسار المرغوب بأقل خطأ ممكن والتغلب على الاضطرابات الديناميكية غير الممثلة بالحصول على تحكم امثل لعزم عجلتي الروبوت اليمنى واليسرى مع استدعاء اقل لدالة التقيم .


Article
USEs OF GA, PSO and MPSO TO BREAK TRANSPOSITION CIPHER SYSTEM: comparative study

Author: Mohamed H. Albawi
Journal: Journal of College of Education مجلة كلية التربية ISSN: 18120380 Year: 2016 Issue: 5 Pages: 207-226
Publisher: Al-Mustansyriah University الجامعة المستنصرية

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Abstract

GA is an adjustable search method that has the ability for search in smart way to find the best solution and trying to reduce the time that required for obtaining the optimal solution. Particle Swarm Optimization (PSO) algorithm emulate the behavior of a swarm of fish and bird flocks. It's a heuristic global optimization method which can be implemented and applying to solve various optimization problems. The most attractive of using PSO is that it has a fast convergence than the other global optimization methods. Modify PSO (MPSO) is a relatively new approach to attacks transposition cipher which it depends on using multi swarms rather than single swarm and allowing the particles in all swarms to exchange information between them in order to obtains the best solution from all swarms. This research focuses on use GA, PSO and MPSO to cryptanalyze transposition cipher based on a new tools to determine the fitness function by calculating the Diagram(DG), Trigram(TG) and Quadgram (QG) frequency of letters. It is shown that such algorithms can be used to reduce the number of trails which are needed to determined the initial states of the attacked systems using ciphertext only attack. Experimental results show the successful applications of GA, PSO and MPSO in cryptanalysis of transposition cipher system. Also, the experimental results indicate that the MPSO is more powerful than the other techniques in cryptanalysis transposition depending on the accuracy of results.


Article
Path Planning of an Autonomous Mobile Robot using Enhanced Bacterial Foraging Optimization Algorithm
تخطيط مسار الروبوتات المتنقلة على أساس خوارزمية النهم للبكتريا المحسنة

Authors: Nizar Hadi Abbas نزار هادي عباس --- Farah Mahdi Ali فرح مهدي علي
Journal: Al-Khwarizmi Engineering Journal مجلة الخوارزمي الهندسية ISSN: 18181171 23120789 Year: 2016 Volume: 12 Issue: 4 Pages: 26-35
Publisher: Baghdad University جامعة بغداد

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Abstract

This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algorithm and other two state-of-the-art algorithms. This study showed that the proposed method is effective and produces trajectories with satisfactory results.

يقدم هذا البحث , وصفا لمشكلة تخطيط مسارالروبوتات المتنقلة في الزمن الحقيقي والمتمثلة بايجاد مسار امثل للروبوت من نقطة بداية والى نقطة نهاية على خريطة مسطحة بشكل مساحة ثنائية الابعاد. قدم خوارزمية محسنة لطريقة النهم للبكتريا لحل مسألت تخطيط المسار. ان هذه الخوارزمية المستوحاة من الطبيعة والتي تقلد عملية بحث عن المؤن لبكتريا مسماة بال ( أي كولاي) استخدمت لايجاد مسار من نقطة بداية الى نقطة نهاية. الخوارزمية المقترحة تم عرضها واثباتها عن طريق محاكاة لنوعين من البيئات المختلفة الثابتة والمتحركة. اجريت مقارنة بين الطريقة المطورة و طريقتين اخريين حديثة. هذا البحث اظهر فاعلية هذه الطريقة المقترحة في ايجاد مسارات بشكل مرضٍ.


Article
Design of a Nonlinear Fractional Order PID Neural Controller for Mobile Robot based on Particle Swarm Optimization

Authors: Ahmed Sabah Al-Araji --- Luay Thamir Rasheed
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2016 Volume: 34 Issue: 12 Part (A) Engineering Pages: 2318-2333
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

The goal of this paper is to design a proposed non-linear fractional order proportional-integral-derivativeneural (NFOPIDN) controller by modifying and improving the performance of fractional order PID (FOPID) controller through employing the theory of neural network with optimization techniquesfor the differential wheeled mobile robotmulti-input multi-output (MIMO) systemin order to follow a desired trajectory. The simplicity and the ability of fast tuning are important features of the particle swarm optimization algorithm (PSO) attracted us to use it to find and tune the proposed non-linear fractional order proportional-integral-derivative neural controller’s parameters and then find the best velocity control signals for the wheeled mobile robot. The simulation results show that the proposed controller can give excellent performance in terms of compared with other works (minimized mean square error equal to 0.131 for Eight-shaped trajectory and equal to 0.619 for Lissajous- curve trajectory as well as minimum number of memory units needed for the structure of the proposed NFOPIDN controller (M=2 for Eight-shaped trajectory and M=4 for Lissajous- curve trajectory) with smoothness of linear velocity signals obtained between (0 to 0.5) m/sec.

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