Comparison of two non-linear model-based control strategies for autonomous vehicles

TL;DR

This paper compares two non-linear model-based control strategies for autonomous vehicles, focusing on their robustness and performance in simulation scenarios.

Contribution

It introduces a comparative analysis of Lyapunov-based and sliding mode control strategies for vehicle path following.

Findings

Sliding mode control shows higher robustness to uncertainties.

High order sliding mode reduces chattering issues.

Both controllers effectively follow paths in simulation.

Abstract

This paper presents the comparison of two non-linear model-based control strategies for autonomous cars. A control oriented model of vehicle based on a bicycle model is used. The two control strategies use a model reference approach. Using this approach, the error dynamics model is developed. Both controllers receive as input the longitudinal, lateral and orientation errors generating as control outputs the steering angle and the velocity of the vehicle. The first control approach is based on a non-linear control law that is designed by means of the Lyapunov direct approach. The second approach is based on a sliding mode-control that defines a set of sliding surfaces over which the error trajectories will converge. The main advantage of the sliding-control technique is the robustness against non-linearities and parametric uncertainties in the model. However, the main drawback of first order sliding mode is the chattering, so it has been implemented a high order sliding mode control. To test and compare the proposed control strategies, different path following scenarios are used in simulation.