Anmin Zhu and Simon X. Yang
Neural dynamics, tracking control, back-stepping control, mobile robot, stability
Tracking control is a key issue for mobile robots, where smooth velocity commands are desirable for the robot navigation. In this paper, a novel tracking controller for real-time navigation of a non-holonomic mobile robot is proposed. This controller integrated the back-stepping model and a biologically inspired neural system model. This control algorithm is derived from the error dynamics analysis of a mobile robot. The stability of the tracking controller is guaranteed by Lyapunov stability theory. Unlike some existing tracking controllers, this proposed controller can solve the velocity jump problem which is caused by a large initial tracking error. It is capable of generating smooth robot control signals with zero velocities at the beginning. In addition, unlike most tracking controllers, the proposed controller removed the unpractical “perfect velocity tracking assumption related to real robots. The effectiveness and efficiency are demonstrated by experimental and comparison studies.
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