Adaptive tracking control of a nonholonomic wheeled mobile robot with multiple disturbances and input constraints

In this paper, an adaptive trajectory-tracking control scheme is proposed for a nonholonomic wheeled mobile robot (NMR) subjected to skidding, slipping, unknown external disturbance, model uncertainties, and input saturation constraints. The changeable unknown external disturbances of the system which are hard to get, and input saturation constraints should be taken into account for safety in reality. An auxiliary system is presented for analyzing the influence of input saturation constraints, and the state of the auxiliary system is integrated into the adaptive controller. In addition, to handle the uncertainty of parameters, the radial basis function neural network (RBFNN) is proposed to deal with the unknown external disturbances of the robot dynamics. Considering slippery conditions, the skidding of the wheels and the slipping of the robots may lead to system instability. The influences of skidding, slipping, and model uncertainties are considered to be a special type of disturbance. Subsequently, a nonlinear disturbance observer is presented and integrated into the adaptive controller. Afterward based on the proposed control techniques, the stability of the robot system is proved through Lyapunov synthesis. Lastly, simulation experiments are carried on to testify to the effectiveness of the adaptive control scheme.