Linear algebra-based controller for trajectory tracking in mobile robots with additive uncertainties estimation

Abstract

Abstract This paper addresses trajectory tracking problem in mobile robots considering additive uncertainties. The controller design method is based on linear algebra theory. Numerical estimation techniques are used to estimate the uncertainty value in each sample time. The controller is calibrated by stochastic way using the Monte Carlo Experiment. In addition, the proof of convergence to zero of the tracking error is included. The theoretical results are validated by simulation and experimental tests. The controller proposed shows that it can be used to reduce the effect of additive uncertainties in the tracking error.