Wheeled mobile robot is influenced inevitably by environment factors. Therefore, Sage-Husa adaptive Kalman
filtering(AKF) is adopted to estimate the reference trajectory with white noise to improve the reality of measurement
information. Meanwhile, by considering the dynamic model of robot and external disturbances, sliding mode is used to
design a torque controller with asymptotic convergence for tracking the estimated value based on the velocity control. The
simulation results show that the proposed control law can overcome measurement noise and external disturbances effectively
and track any reference trajectories quickly.