Tracking Control of Mobile Robots Based on Improved RBF Neural Networks

A control scheme for dynamic tracking of mobile robots is presented, which integrates a velocity controller based on backstepping techniques and a torque controller based on improved RBF neural networks. Because the torque control strategy derived from sliding modes depends on the dynamics of mobile robots, the robustness of the system cannot be guaranteed due to the uncertainties of robot dynamics. In order to decrease the impact of the uncertainties and improve the robustness of the system, improved RBF neural networks are designed online to model the dynamics of mobile robot. Thus the torque controller based on sliding mode is composed of a neural network controller and a robust compensator. Simulations demonstrate the efficacy of the proposed system for robust tracking of mobile robots