Adaptive Tracking Control of Nonholonomic Mobile Robots With Input Constraints and Unknown Disturbance

Abstract

This paper addresses a trajectory-tracking control problem for nonholonomic mobile robots by proposing an adaptive control method in handling kinematic and dynamic constraints. At first, the Euler-Lagrange equation and some corresponding transformations about state variables are used to achieve the design of the robot dynamics system. Then, in designing an adaptive controller, the radial basis function neural network is adopted to obtain the approximate value of the unknown disturbance of the robot dynamics, which makes external disturbance controllable. Besides, the Integral Barrier Lyapunov Function is developed to handle the actuator input saturation, which makes the input matrix bounded. Moreover, according to the Lyapunov second method, the stability of the closed-loop mobile robot system has been proved. Finally, to prove the feasibility of the adaptive control method, simulation experiments are carried out.