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Article
Searching for Goal by Mobile Robot with Collision-Free Motion in Unknown Environment

Authors: Turki Y. Abdalla تركي يونس عبد الله --- Seaar J. Al_Duboni سُئار جواد الدبوني
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2012 Volume: 12 Issue: 2 Pages: 89-100
Publisher: Basrah University جامعة البصرة

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Abstract

Obstacle avoidance and path planning are from the most important problems in mobile robots, especially in unknown environment . In this paper, we proposed an approach for mobile robot navigation combining path planning and obstacle avoidance. Methods such as obstacle avoidance are inspired from the nature, and have been developed by fuzzy logic to train an intelligent robot in unknown environment. The model of the robot has two driving wheels and the linear velocity and azimuth of the two wheels are independently controlled using PID controller. Inputs are obtained from ultrasonic sensors mounted on it.

تجنّب العقابت إثناء حركةِ الروبوت النقال مِنْ المشاكلِ الأكثر أهميةً، خصوصاًفي البيئاتِ غير المعروفة. في هذا البحث، تم اقتراح أسلوب من اجل الملاحة التيتَدْمجُ جزءان منفصلان هما تخطيط الطريق إلى الهدف وتجنّبِ عق ا بت إثناء الح رك ة وذلك من خلال تطوير جهاز سيطرةِ ضبابيِ . إن الروبوت النقَّالَ د يرك البيئة منخلال ستّة عشرَ متحسس من نوع سونارَ ( موجات فوق الصّوتية)؛ هذهالمتحسسات مثبتة حول الجسمِ . إنّ الإستراتيجياتَ التفاعليةَ المستعملة في هذهالبحث أستندت على المعلوماتِ الحسّيةِ ا ف لوق الصّوتيةِ والتفاعلاتِ الآنيةِ النسبيةِبين الروبوت ﻴﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا ﻴﱠِِﻨﻟﻘﺠﺔﺒﺎﺌولا لﱠِِهولةِ . تم تصميم محاكي الروبوت النقَّالِ لإختِبار ﻤ ﻤ ﻤ ﻤ ﻤ ﻤ ﻤ ﻤ ﻤﻤﻤﻤ ﻤ وتَطبيق أنظمةِ السيطرةَ بالإضافة إلى معرفة سلوكَ ه في البيئاتِ المختلفةِ . يحتوي نموذج الروبوت النقَّالِ على عجلتي قيادة حيث يتم السيطرة على العجلتين من خلال زاويةوذلك بواسطة جهازي سيطرة من (Velocity ) و سرعته (Azimuth ) ميل الروبوتمن أجل حصول (Genetic Algorithm ) تم استعمال الخوارزمية الوراثية .(PID) نوعلتتبع طريقِ الإنسان الآلي النقَّال. (PID) على أفضل تصميم لمسيطر


Article
A Cognitive PID Neural Controller Design for Mobile Robot Based on Slice Genetic Algorithm
تصميم مسيطر عصبي تناسبي تكاملي تفاضلي مدرك لإنسان آلي متنقل مبني على أساس خوارزمية الشرائح الجينية

Author: Ahmed Sabah Al-Araji
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2015 Volume: 33 Issue: 1 Part (A) Engineering Pages: 208-222
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

The main core of this paper is to design a trajectory tracking control algorithm for mobile robot using a cognitive PID neural controller based slice genetic optimization in order to follow a pre-defined a continuous path. Slice Genetic Optimization Algorithm (SGOA) is used to tune the cognitive PID neural controller's parameters in order to find best velocities control actions of the right wheel and left wheel for the mobile robot. Pollywog wavelet activation function is used in the structure of the cognitive PID neural controller. Simulation results and experimental work show the effectiveness of the proposed cognitive PID neural tuning control algorithm; This is demonstrated by the minimized tracking error and the smoothness of the velocity control signal obtained, especially with regards to the external disturbance attenuation problem.

أن المحور الرئيسي لهذا البحث هو تصميم خوارزمية مسيطر تتابع مسار لإنسان آلي متنقل باستخدام مسيطر عصبي تناسبي تكاملي تفاضلي أساسه أمثلية الشرائح الجينية لكي يتبع مسار مستمر معرف مسبقا.لقد تم استخدام خوارزمية الشرائح الجينية لتنغيم عناصر المسيطر العصبي التناسبي التكاملي التفاضلي المدرك لكي يجد أفضل أشارة سرعة للإنسان الآلي المتحرك. أن الدالة الفعالة التي استخدمت في هيكلية المسيطر العصبي التناسبي التكاملي التفاضلي المدرك هي (Pollywog wavelet).من خلال نتائج المحاكاة والأعمال التجريبية, أن فعالية خوارزمية تنغيم المسيطر المقترح تقوم بتقليل الخطأ ألتتابعي لمسار الإنسان الآلي المتحرك مع توليد أشارة سرعة ناعمة, برغم من وجود التأثير الاضطرابي الخارجي.


Article
Cognitive Neural Controller for Mobile Robot

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Abstract

Abstract – This paper proposes a cognitive neural controller to guide a nonholonomic mobile robot during continuous and non-continuous trajectory tracking and to navigate through static obstacles with collision-free and minimum tracking error. The structure of the controller consists of two layers; the first layer is a neural network topology that controls the mobile robot actuators in order to track a desired path based on back-stepping technique and posture identifier. The second layer of the controller is cognitive layer that collects information from the environment and plans the optimal path. In addition to this, it detects if there is any obstacle in the path so it can be avoided by re-planning the trajectory using particle swarm optimization (PSO) technique. The stability and convergence of control system are proved by using the Lyapunov criterion. Simulation results and experimental work show the effectiveness of the proposed cognitive neural control algorithm; this is demonstrated by minimizing tracking error and obtaining the smooth torque control signal, especially when the robot navigates through static obstacles with collision-free and the external disturbances applied.


Article
Design a Fuzzy PID Controller for Trajectory Tracking of Mobile Robot

Authors: M.J. Mohamed --- M.Y. Abbas
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 1 Part (A) Engineering Pages: 100-110
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

In this paper, a trajectory tracking control for a non-holonomic differential wheeled mobile robot (WMR) system is presented. A big number of investigations have been used the kinematic model of mobile robot which is a nonlinear model in nature, thus a hard task to control it. This work focuses on the design of fuzzy PID controller tuned with a firefly optimization algorithm for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller's parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with the least possible value of error. Matlab Simulation results show that a good performance and robustness of the controller. This is confirmed by the value of minimized tracking error and the smooth velocity especially concerning presence of external disturbance or change in initial position of mobile robot.


Article
Design of a Nonlinear PID Neural Trajectory Tracking Controller for Mobile Robot based on Optimization Algorithm
تصميم مسيطر تتابع مسار عصبي لأخطي تناسبي تكاملي تفاضلي لإنسان آلي متنقل مبني على أساس الخوارزمية ألأمثليه

Authors: Khulood E. Dagher --- Ahmed Al-Araji
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2014 Volume: 32 Issue: 4 Part (A) Engineering Pages: 973-985
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

This paper presents a trajectory tracking control algorithm for a non-holonomic wheeled mobile robot using optimization technique based nonlinear PID neural controller in order to follow a pre-defined a continuous path. As simple and fast tuning algorithms, particle swarm optimization algorithm is used to tune the nonlinear PID neural controller's parameters to find best velocity control actions for the mobile robot. Simulation results show the effectiveness of the proposed nonlinear PID control algorithm; this is demonstrated by the minimized tracking error and the smoothness of the velocity control signal obtained, especially with regards to the external disturbance attenuation problem.

يقدم هذا البحث, خوارزمية المسيطر ألتتابعي لمسار عجلة الإنسان الآلي المتحرك باستخدام التقنية ألأمثليه أساسه المسيطر التناسبي التكاملي التفاضلي العصبي اللاخطي لكي يتبع مسار مستمر معرف مسبقا. أن الخوارزمية المستخدمة تتميز بسرعة وببساطة تنغيم عناصر المسيطر اللاخطي التناسبي التكاملي التفاضلي وذلك باستخدام خوارزمية حشد الجسيمات ألأمثليه وإيجاد أفضل أشارة سرعة للإنسان الآلي المتحرك. من خلال نتائج المحاكاة, أن فعالية خوارزمية المسيطر اللاخطي المقترح تقوم بتقليل الخطأ ألتتابعي لمسار الإنسان الآلي المتحرك مع توليد أشارة سرعة ناعمة, برغم من وجود التأثير الاضطرابي الخارجي.


Article
Design Interval Type-2 Fuzzy Like (PID) Controller for Trajectory Tracking of Mobile Robot

Authors: Mustafa Y. Abbas --- Mohamed J. Mohamed
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2019 Volume: 19 Issue: 3 Pages: 1-15
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

One of the major problems in the field of mobile robots is the trajectory tracking problem. There are a big number of investigations for different control strategies that have been used to control the motion of the mobile robot when the nonlinear kinematic model of mobile robots was considered. The trajectory tracking control of autonomous wheeled mobile robot in a changing unstructured environment needs to take into account different types of uncertainties. Type-1 fuzzy logic sets present limitations in handling those uncertainties while type-2 fuzzy logic sets can manage these uncertainties to give a superior performance. This paper focuses on the design of interval type-2 fuzzy like proportional-integral-derivative (PID) controller for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller’s parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with minimum tracking error. The Matlab simulation results demonstrate the good performance and robustness of this controller. These were confirmed by the obtained values of the position tracking errors and a very smooth velocity, especially with regards to the presence of external disturbance or change in the initial position of mobile robot. Finally, in comparison with other proposed controllers, the results of nonlinear IT2FLC PID controller outperform the nonlinear PID neural controller in minimizing the MSE for all control variables and in the robustness measure.


Article
Design of On-Line Nonlinear Kinematic Trajectory Tracking Controller for Mobile Robot based on Optimal Back-Stepping Technique

Author: Asst. Prof. Dr. Ahmed Sabah Al-Araji
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2014 Volume: 14 Issue: 2 Pages: 25-36
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Abstract –This paper presents an on-line nonlinear trajectory tracking control algorithm for differential wheeled mobile robot using optimal back-stepping technique based particle swarm optimization while following a pre-defined continuous path. The aim of the proposed feedback nonlinear kinematic controller is to find the optimal velocity control action for the real mobile robot. The particle swarm optimization algorithm is used to find the on-line optimal parameters for the proposed controller based on the Lyapunov criterion in order to check the stability of the control system. Simulation results (Matlab) and experimental work (LabVIEW) show the effectiveness and robustness of the proposed on-line nonlinear kinematic control algorithm. This is demonstrated by minimizing tracking error and obtaining smoothness of the optimal velocity control signal, especially with regards to the external disturbance attenuation problem..Keywords:- Mobile Robots, Nonlinear Kinematic Controller, Back-Stepping Technique, Particle Swarm Optimization, Trajectory Tracking, Matlab package, LabVIEW package.


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.


Article
Motion Control of An Autonomous Mobile Robot using Modified Particle Swarm Optimization Based Fractional Order PID Controller

Authors: Ghusn A. Ibraheem --- Ibraheem K. Ibraheem
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2016 Volume: 34 Issue: 13 Part (A) Engineering Pages: 2406-2419
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

This paper presents a comparison between two nonlinear PID controllers, the first is the Neural based controller and the second is the nonlinear fractional order PID controller (FOPID) for a trajectory tracking control of a non-holonomic two wheeled mobile robots (2-WMR). A modified particle swarm optimization (MPSO) has been proposed in this work to tune the parameters of the nonlinear FOPID controller to design the controller so that the 2-WMR follows exactly a predefined continuous track. The kinematic model of a differential drive 2-WMR has been derived to simulate the behavior of the 2-WMR and it is used in the design and simulations of the proposed FOPID controller. From simulation and results, it can be seen that the efficiency of the proposed nonlinear FOPID controller outperforms the nonlinear integer order PID controller; this is proved by the minimized tracking error and the speed control signals obtained.


Article
A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
دراسة مقارنة لخوارزميات ذكية متنوعة أساسه مسيطر تتابع مسار عصبي لأخطي تناسبي تكاملي تفاضلي لنموذج التحرك التفاضلي لإنسان آلي متنقل.

Author: Ahmed Sabah Al-Araji أحمد صباح عبد الأمير الأعرجي
Journal: Journal of Engineering مجلة الهندسة ISSN: 17264073 25203339 Year: 2014 Volume: 20 Issue: 5 Pages: 44-60
Publisher: Baghdad University جامعة بغداد

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Abstract

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO learning algorithm is more effective and robust than genetic learning algorithm; this is demonstrated by the minimized tracking error and obtained smoothness of the velocity control signal, especially when external disturbances are applied.

يقدم هذا البحث, دراسة مقارنة لخوارزميتين لتعليم مسيطر تناسبي تكاملي تفاضلي عصبي لاخطي تتابعي لمسار عجلة الإنسان آلي متحرك لكي يتبع مسار مستمر معرف مسبقا. كتقنيات سهله وسريعة التنغيم, لقد تم استخدام الخوارزمية الوراثية وخوارزمية حشد الجسيمات الامثلية لتنغيم عناصر المسيطر اللاخطي التناسبي التكاملي التفاضلي لإيجاد أفضل أشارة سرعة لعجلة للإنسان الآلي المتحرك الحقيقي. لقد تم استخدام الدالة الفعالة موجة البوليونك في هيكلية المسيطر العصبي. من خلال نتائج المحاكاة والعمل التجريبي, أثبتت أن المسيطر التناسبي التكاملي التفاضلي العصبي اللاخطي المقترح تنغيمه بواسطة خوارزمية حشد الجسيمات الامثلية أكثر فعالية و متانة مقارنة بالمسيطرة الذي تم تنغيمه بواسطة الخوارزمية الوراثية, وهذا واضح من خلال تقليل الخطأ ألتتابعي لمسار الإنسان الآلي المتحرك مع توليد أشارة سرعة ناعمة, برغم من وجود التأثير الاضطرابي الخارجي.

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