Asymptotic tracking control of uncertain nonholonomic wheeled mobile robot with actuator saturation and external disturbances

摘要

This paper deals with the asymptotic tracking control for the uncertain nonholonomic wheeled mobile robot system subjected to actuator saturation and external disturbances simultaneously. A dynamic system is introduced to deal with the actuator saturation, radial basis function neural networks (RBF NNs) are employed to approximate the unknown closed-loop system dynamics, and an adaptive sliding mode feedback term is used to compensate for the approximation error as well as external disturbances. Consequently, a novel adaptive neural controller is designed to guarantee the stability of the closed-loop system and the asymptotic convergence of tracking errors. Meanwhile, the convergence of NN weights is verified, which means that accurate approximation of the unknown closed-loop system dynamics can be obtained and the constant weights can be reused to perform the same or similar control tasks. Finally, simulation studies illustrate the effectiveness of the proposed scheme.

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