Trajectory Tracking of Autonomous Vehicles using Different Control Techniques(PID vs LQR vs MPC)
B.S. Krishna Varma, Nitin Swamy, Sujoy Mukherjee
Abstract
One of the Key Technology used for Autonomous Driving is "Trajectory Tracking and Planning". the prior safety actions should be taken for Roll-Over Stability Control and Yaw Stability Control where the Majority of car crashes and accidents takes place. In this paper we developed a mathematical driver model for trajectory tracking in autonomous driving. We designed control algorithms in order to track a given trajectory using different control techniques like a classical PID (Proportional Integral Derivative) controller and some advanced control techniques like LQR (Linear Quadratic Regulator) and MPC (Model Predictive Control) which are dynamic controllers. Efforts have been made to perform closed loop simulation in MATLAB, this paper gives a crisp comparison about performance of each controller. This simulation results indicate that the mathematical driver model successfully replicate's human driving performance and can be used for dynamics analysis of vehicle. This research compares different controllers' performances for trajectory tracking in autonomous driving.