Adaptive State Feedback Trajectory Tracking Control of a Car-Like Drive Wheeled Mobile Robot Using RBF Neural Network

This paper presents an adaptive-neural trajectorytracking controller for a nonholonomic wheeled mobile robot in presence of parametric and nonparametric uncertainty in model. A Lyapunov-based stability analysis is utilised to guarantee that tracking and state estimation errors are uniformly ultimately bounded. The proposed control algorithms are applied to a car-like drive wheeled mobile robots and simulation results are presented to illustrate the effectiveness of the proposed control law.

کلیدواژه ها:

Adaptive-neural control ، RBF ، nonholonomic WMR ، trajectory tracking ،