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Article
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
تصميم وحدة سيطرة حركية عصبية لتتبع مسار الروبوتات المتنقلة بعجلات على أساس المحسن الهجين بين خوارزمية اليرعات المضيئة وخوارزمية خلية النحل

Authors: Nizar Hadi Abbas نزار هادي عباس --- Basma Jumia saleh بسمة جمعة صالح
Journal: Al-Khwarizmi Engineering Journal مجلة الخوارزمي الهندسية ISSN: 18181171 23120789 Year: 2016 Volume: 12 Issue: 1 Pages: 45-60
Publisher: Baghdad University جامعة بغداد

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Abstract

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is implemented based on hybrid Crossoved Firefly Algorithm with Artificial Bee Colony (CFA-ABC) to tune the controller's parameters to achieve the optimal path. The performance of the hybrid optimization algorithm is verified by various benchmark functions. The simulation results show that the utilizing of CFA and (CFA-ABC ) are better than the original Firefly Algorithm. A simulation example is given to indicate the effectiveness of the proposed algorithm, the results have been done using MATLAB (R2013b), and all trajectory tracking results with two reference trajectories (circular and lemniscates ) are presented.

يقدم هذا البحث , تصميما مسيطرا لتتبع مسار عجلة الانسان الالي المتحرك المبني على أساس مسيطر تكاملي حركي عصبي لتوجيه الروبوت المحمول المصنع من قبل شركة National Instrument , الغاية من المسيطر هي تقريب السرعة الحقيقية للأنسان الالي اقرب ما يكون من السرعة المطلوبة بجعل مقدار معدل الخطا اقرب الى الصفر. المسيطر المقترح في هذا البحث يتكون من طبقتين: الطبقة الأولى هي نظام شبكة عصبية متعدد الطبقات لتتبع المسار المطلوب و الطبقة الثانية هي طبقة الخوارزمية الأمثلية والتي تشمل خوارزمية هجينة محسنة وهي مكونة من خوارزمية اليرعات المضيئة وخوارزمية خلية النحل وتستخدم لأيجاد أفضل قيم للمسيطر والوصول للمسار الامثل. من خلال نتائج المحاكاة, اثبت المسيطر المقترح وخوارزمية الامثلية كفاءتهما بالوصول الى مقدار خطا وبأقل قيمة وتمت المحاكاة بأستخدام برنامج الماتلاب وتم تطبيقها على نوعين من المسارات (الدائري والانفنتي).


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.

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