Table of Contents
ISRN Applied Mathematics
Volume 2014 (2014), Article ID 634936, 9 pages
Research Article

Wheeled Mobile Robot RBFNN Dynamic Surface Control Based on Disturbance Observer

1State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China
2Department of Mechanical Engineering, Chongqing Aerospace Polytechnic College, Chongqing 400021, China

Received 13 November 2013; Accepted 9 December 2013; Published 11 February 2014

Academic Editors: X.-G. Yan and X.-S. Yang

Copyright © 2014 Shaohua Luo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper focuses on the problem of an adaptive neural network dynamic surface control (DSC) based on disturbance observer for the wheeled mobile robot with uncertain parameters and unknown disturbances. The nonlinear observer is used to compensate for the external disturbance, and the neural network is employed to approximate the uncertain and nonlinear items of system. Then, the Lyapunov theory is introduced to demonstrate the stabilization of the proposed control algorithm. Finally, the simulation results illustrate that the proposed algorithm not only is superior to conventional DSC in trajectory tracking and external friction disturbance compensation but also has better response, adaptive ability, and robustness.