Adaptive control and data fusion using EKF for wheeled robots with parametric uncertainties
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This paper considers the tracking-control problem of a nonholonomic wheeled mobile robot with both parameter and nonparameter uncertainties. A robust adaptive controller is proposed with the aid of the adaptive backstepping technique and the learning ability of neural networks. The proposed controller guarantees that the tracking error converges to a small hall containing the origin. The hall's radius can be adjusted by control parameters. The proposed controller is successfully implemented in our simulator.