Robust Trajectory Tracking Error Model-Based Predictive Control for Unmanned Ground Vehicles

TL;DR

This paper introduces a robust model predictive control method for unmanned ground vehicles that effectively tracks complex trajectories with minimal error by integrating error-based modeling, feedforward, and robust control strategies.

Contribution

It presents a novel robust trajectory tracking error-based control approach combining model predictive control with feedforward and robust control for unmanned ground vehicles.

Findings

Effective tracking of linear and curvilinear trajectories

Low tracking error demonstrated in experiments

Robust control enhances trajectory accuracy

Abstract

This paper proposes a new robust trajectory tracking error-based control approach for unmanned ground vehicles. A trajectory tracking error-based model is used to design a linear model predictive controller and its control action is combined with feedforward and robust control actions. The experimental results show that the proposed control structure is capable to let a tractor-trailer system track both linear and curvilinear target trajectories with low tracking error.