Optimal LPV-based Control and Estimation for Autonomous Vehicles

Abstract

This article presents an approach to address the problem of designing advanced control and estimation techniques for the autonomous driving guidance. In particular, this work takes advantage of the properties of polytopic LPV systems and predictive optimal control to guide the vehicle along a planned trajectory. Linear Parameter Varying (LPV) theory is used to model the dynamics of the vehicle and implement an LPV-Model Predictive Controller (LPV-MPC) that can be computed online with reduced computational cost. Furthermore, the LPV framework is used to design an optimal observer that estimates vehicle variables that cannot be measured. The control and estimation scheme is validated in simulation using the Robotic Operating System (ROS) framework where its effectiveness is demonstrated.