Robust tube-based LPV-MPC for autonomous lane keeping

TL;DR

This paper introduces a robust tube-based LPV-MPC control architecture for autonomous lane keeping, effectively handling uncertainties in longitudinal speed predictions to improve lateral control performance.

Contribution

It presents a novel tube-based LPV-MPC approach that accounts for longitudinal speed uncertainties in autonomous lane keeping, enhancing robustness over existing methods.

Findings

Successful simulation validation of the proposed control scheme.

Improved lane keeping robustness under speed prediction uncertainties.

Effective handling of LPV system uncertainties in autonomous driving.

Abstract

This paper proposes a control architecture for autonomous lane keeping by a vehicle. In this paper, the vehicle dynamics consist of two parts: lateral and longitudinal dynamics. Therefore, the control architecture comprises two subsequent controllers. A longitudinal model predictive control (MPC) makes the vehicle track the desired longitudinal speeds that are assumed to be generated by a speed planner. The longitudinal speeds are then passed to a lateral MPC for lane keeping. Due to the dependence of the lateral dynamics on the longitudinal speed, they are represented in a linear parameter-varying (LPV) form, where its scheduling parameter is the longitudinal speed of the vehicle. In order to deal with the imprecise information of the future longitudinal speed (the scheduling parameter), a bound of uncertainty is considered around the nominal trajectory of the future longitudinal velocities. Then, a tube-based LPV- MPC is adopted to control the lateral dynamics for attaining the lane keeping goal. In the end, the effectiveness of the proposed methods is illustrated by carrying out simulation tests.