LPV-MPC control of autonomous vehicles

In this work, a novel approach is presented to solve the trajectory tracking problem for autonomous vehicles. This method is based on the use of a cascade control where the external loop solves the position control using a novel Linear Parameter Varying - Model Predictive Control (LPV-MPC) approach and the internal loop is in charge of the dynamic control of the vehicle using a LPV - Linear Quadratic Regulator technique designed via Linear Matrix Inequalities (LPV-LMI-LQR). Both techniques use an LPV representation of the kinematic and dynamic models of the vehicle. The main contribution of the LPV-MPC technique is its ability to calculate solutions very close to those obtained by the non-linear version but reducing significantly the computational cost and allowing the real-time operation. To demonstrate the potential of the LPV-MPC, we propose a comparison between the non-linear MPC formulation (NL-MPC) and the LPV-MPC approach.This work has been partially funded by the Spanish Governmentand FEDER through the projects CICYT DEOCS and SCAV (refs.MINECO DPI2016-76493, DPI2017-88403-R). This work has alsobeen partially funded by AGAUR of Generalitat de Catalunyathrough the Advanced Control Systems (SAC) group grant (2017SGR 482), and by AGAUR and the Spanish Research Agencythrough the Maria de Maetzu Seal of Excellence to IRI (MDM-2016-0656).Peer Reviewe