Gain-scheduling LPV control for autonomous vehicles including friction force estimation and compensation mechanism

Abstract

This study presents a solution for the integrated longitudinal and lateral control problem of urban autonomous vehicles. It is based on a gain-scheduling linear parameter-varying (LPV) control approach combined with the use of an Unknown Input Observer (UIO) for estimating the vehicle states and friction force. Two gain-scheduling LPV controllers are used in cascade configuration that use the kinematic and dynamic vehicle models and the friction and observed states provided by the Unknown Input Observer (UIO). The LPV-UIO is designed in an optimal manner by solving a set of linear matrix inequalities (LMIs). On the other hand, the design of the kinematic and dynamic controllers lead to solve separately two LPV-Linear Quadratic Regulator problems formulated also in LMI form. The UIO allows to improve the control response in disturbance affected scenarios by estimating and compensating the friction force. The proposed scheme has been integrated with a trajectory generation module and tested in a simulated scenario. A comparative study is also presented considering the cases that the friction force estimation is used or not to show its usefulness.