Comparative Analysis of Controllers for Autonomous Vehicle Steering

• Bruno Campos Trovatti UFSCar
• Giovani Bruno Cicone UFSCar
• Lucas Barbosa Marcos UFSCar

Resumo

Technological advances in recent years have allowed major developments in the field of autonomous vehicles. This technology has proven to be increasingly reliable and efficient in reducing accidents and optimizing transportation resources. However, it is a rapidly developing area, and comparative studies are still needed to clarify the advantages and disadvantages of each type of controller in different use cases. This article addresses the development of steering control for autonomous vehicles by comparing the classic PID control technique and the modern control techniques using a Robust Linear Quadratic Regulator. The objective is to assess the advantages and disad-vantages of each of these controllers when applied to automotive models in a numerical simulation environment. PID, nominal LQR, and robust LQR controllers were designed and applied to autonomously drive the car along a reference path. The simulated results show the highest efficiency in the nominal LQR controller when there are no car parameter variations, the PID controller shows performance degradation with mass variations, while the Robust LQR controller maintains its performance. Therefore, applications that are subject to high parametric uncertainties are better served by the robust LQR controller.

Palavras-chave: Uncertainty, Regulators, Numerical simulation, Robustness, Automobiles, Autonomous vehicles, Robots, Physics, Vehicles, Resilience, Autonomous Vehicles, Robotics, Control Systems, Numerical Simulation, Vehicle Steering