Application of a stabilizing model predictive controller to path following for a car-like agricultural robot

This work addresses the problem of path following for a car-like agricultural robot by means of a finite control set model predictive control (FCS-MPC) strategy that considers the control actions in a set composed of a limited amount of elements. Recent results on a stabilizing MPC formulation that replaces the classical control invariant set by a pair of inner-outer sets are extended to preserve stability properties with different control and prediction horizons and are then used for the aforementioned application. Being particularly simple, the presented approach can explicitly deal with nonlinearities and constraints at the expense of resolution in the vehicle steering system, which in practice does not affect the controller performance as will be shown. In addition to describing the control method, simulations and a comparison with another nonlinear MPC strategy are presented to illustrate the advantages of the proposed scheme. Previous theoretical results on a stabilizing MPC scheme based on two regions that replace the traditionally used invariant set are extended. Then, a practical application of path following for a car like robot in agricultural environments is addressed with the proposed control approach, in particular considering a finite control set. Results of realistic simulations are finally presented to analyze the performance of our strategy and to compare it with a classical nonlinear MPC controller. image