This study presents apassivity-based robust switching control for the posture stabilization of wheeled mobile robots (WMRs) with model uncertainty. Essentially, this proposed strategy is switching between (1) passivity-based robust control to lead the robot to the neighborhood of local minima with a finite time and (2) another robust control to perturb the w
-rotational motion of the WMR before the v
-kinetic energy of the WMR become meaningless, thereby, eventually converging to the desired posture. Thus, combining two switching control laws ensures the global convergence of (x
)-navigation of WMRs from any initial position to desired set. Especially, the inter-switching time is intentionally selected before the WMR completely loses its mobility, which ensures a strict decrease in (x
)-navigation potential energy and a better global convergence rate. In addition, this control architecture also includes model uncertainty compensation, often neglected in practice, and analytical study of rotational perturbation was also conducted. The Lyapunov technique and energetic passivity were utilized to derive this control law. Simulation results are presented to illustrate the effectiveness of the proposed technique. It was found from the results that the WMR was quickly converged to the desired posture even under the presence of model uncertainty.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited