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Comparative Study of Inspired Algorithms for Trajectory-Following Control in Mobile Robot
Author(s) -
Basma Jumaa Saleh,
Ali Talib Qasim al-Aqbi,
Ahmed Yousif Falih Saedi,
Lamees abdalhasan Salman
Publication year - 2018
Publication title -
international journal of modern education and computer science
Language(s) - English
Resource type - Journals
eISSN - 2075-017X
pISSN - 2075-0161
DOI - 10.5815/ijmecs.2018.09.01
Subject(s) - firefly algorithm , computer science , control theory (sociology) , trajectory , backstepping , controller (irrigation) , kinematics , mobile robot , nonlinear system , robot , nonholonomic system , acceleration , lyapunov function , particle swarm optimization , algorithm , control (management) , artificial intelligence , adaptive control , physics , astronomy , classical mechanics , quantum mechanics , agronomy , biology
This paper is devoted to the design of a trajectory-following control for a differentiation nonholonomic wheeled mobile robot. It suggests a kinematic nonlinear controller steer a National Instrument mobile robot. The suggested trajectory-following control structure includes two parts; the first part is a nonlinear feedback acceleration control equation based on backstepping control that controls the mobile robot to follow the predetermined suitable path; the second part is an optimization algorithm, that is performed depending on the Crossoved Firefly algorithm (CFA) to tune the parameters of the controller to obtain the optimum trajectory. The simulation is achieved based on MATLAB R2017b and the results present that the kinematic nonlinear controller with CFA is more effective and robust than the original firefly learning algorithm; this is shown by the minimized trackingfollowing error to equal or less than (0.8 cm) and getting smoothness of the linear velocity less than (0.1 m/sec), and all trajectoryfollowing results with predetermined suitable are taken into account. Stability analysis of the suggested controller is proven using the Lyapunov method.

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