This paper presents the design, implementation and comparative analysis of an intelligent neural network based controller used for adaptive trajectory tracking of a wheeled mobile robot with unknown dynamics. In this proposed control scheme, the neural network is used to continuously tune the gains of the kinematic based controller in a backstepping structure. The online learning and adaptive capabilities of the neural network are utilized to achieve a smooth and fast robot tracking motion. The simulation results are used to verify the tracking performance of the proposed control algorithm and to compare it with the conventional backstepping controller.

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