<p>This paper deals with the constrained control of an autonomous wheeled mobile robot for accurate trajectory tracking, considering model uncertainties, external disturbances and measurement errors. Primarily, a novel scheme is employed to accurately estimate the perturbed dynamic model of a wheeled robot by incorporating complementary terms. These terms are computed to compensate for perturbations utilizing the information of mass center acceleration and angular velocity of robot. To reduce the measurement errors, comprising noise and bias, the study proposes a fusion of acceleration and angular velocity with an aided system data through stochastic analysis. In this respect, an adaptive solution for adjusting the estimator coefficient is introduced to enable effective data fusion. Subsequently, a continuous predictive controller is developed using the constructed nonlinear dynamic model for accurate trajectory tracking of wheeled robot. The constrained stability is presented statistically to prove the boundedness of constrained solution. The simulation results demonstrate the high efficiency of the proposed system in controlling the robot under different scenarios. Moreover, the comparative results with prevalent control algorithms indicate the superior efficiency of the suggested controller in rejecting perturbations under limited control inputs.</p>