LPV-MPC Control for Autonomous Vehicles

Eugenio Alcalá, Vicenç Puig, Joseba Quevedo

IFAC-PapersOnLine · 2019 · 81 citations · 13 references

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Abstract

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.

References

13