Numerical experiments with multistep model-predictive control approaches and sensitivity updates for the tracking control of cars

Abstract

The paper discusses multistep nonlinear model-predictive control (NMPC) schemes for the tracking of a car model along a given reference track. In particular we will compare the numerical performance and robustness of classic single step NMPC, multistep NMPC without re-optimization, multistep NMPC with re-optimization, and multistep NMPC with sensitivity updates instead of a full re-optimization.