Robust Laguerre based model predictive control of nonholonomic mobile robots under slip conditions

Abstract

This paper studies the trajectory tracking of a nonholonomic mobile robot. A robust model predictive control based on Laguerre parametrization is proposed. The slip parameter is the source of uncertainty in the constrained mobile robot and is modeled with the bounded additive disturbance. By designing tubes as the positive disturbance invariant set around the nominal robot trajectory, the trajectory tracking is achieved robust to the introduced disturbances. Using Laguerre functions for input signal parametrization in the tube-based model predictive control structure, it is demonstrated that it does remain real-time with better tracking performance. Furthermore, stability is guaranteed with a sub-optimal procedure. Illustrative simulations are presented to show the applicability of the proposed method.