Rigid-Tube Nonlinear Model Predictive Control for Path Following
While rigid-tube model predictive control introduces robustness with respect to bounded uncertainty, its application to reference tracking may result in poor control performance due to improper reference-trajectory design or disturbances. To circumvent this, the combination of path-following and rigid-tube model predictive control is proposed for systems that require merely a geometric transition without an additional time specification. Therefore, we present results on how to combine rigid-tube model predictive control and path-following. Furthermore, we show for a nonlinear system that the proposed control method steers the system, subject to disturbances, to a robust positive invariant set around the path, while repeated feasibility, stability, and convergence can be guaranteed under mild assumptions. Moreover, the effectiveness and gained flexibility of the predictive controller in handling disturbances is demonstrated in a simulation example considering an autonomous mobile robot.