Asst. Prof. Dr. Ahmed S. Al-Araji; M. Sc. Khulood E. Dagher
Volume 15, Issue 1 , April 2015, , Page 46-60
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; ...
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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.
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.