Asst. Prof. Dr. Ahmed Sabah Al-Araji
Volume 14, Issue 2 , August 2014, , Page 25-36
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 ...
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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.
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Keywords:- Mobile Robots, Nonlinear Kinematic Controller, Back-Stepping Technique, Particle Swarm Optimization, Trajectory Tracking, Matlab package, LabVIEW package.
Yasmin Abdul Ghani Abdul Kareem; Dr. Ahmed Khalaf Hamoudi; Ahmad Saeed Mohammad
Volume 13, Issue 2 , August 2013, , Page 19-25
Abstract
Abstract –A fast, simple and effective method to recognize different hand writing
numbers is presented. Hand writing recognition took high attention in the recent years
by researcher of the intelligent systems, since it can be used in many applications such
as car plate recognition and bank account ...
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Abstract –A fast, simple and effective method to recognize different hand writing
numbers is presented. Hand writing recognition took high attention in the recent years
by researcher of the intelligent systems, since it can be used in many applications such
as car plate recognition and bank account checking. The purpose of this paper is to
develop a method for hand writing numbers detection by using artificial neural network.
The suggested work is divided mainly into four stages and is proposed to resolve the
digits number (i.e., hand writing numbers). Image sample of hand writing numbers is
acquired by a digital camera or scanner, and then it is converted by using the suggested
work which is consisted of four stages to resolve digits. Artificial neural network
(ANN) was applied to recognize the hand writing numbers. Learning method of the
ANN is back propagation and all process handled by MATLAB language.