Neural network-based robust adaptive control of mobile robot with nonholonomic constraints

Abstract

In the trajectory tracking of nonholonomic mobile robot,for solving the unknown factors of mobile robot,such as parametric and nonparametric uncertainties of the kinematics and dynamic models,a robust adaptive controller based on neural network is proposed,which includes a kinematics controller and a dynamic controller.Radial basis function neural network with adaptive parameter is uesed for modeling unknown parts of the kinematics model,and the dynamic controller is based on single-layer neural network with on-line adjustment of weights and adaptive robust controller.The proposed controller can overcome the uncertainties and the disturbances.The system stability and the convergence of tracking system are proved by Lyapunov stability theory.Simulation results show the effectiveness of the proposed tracking control law.