Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm
Carolina Rengifo, Jean-Rémy Chardonnet, Hakim Mohellebi, Damien Paillot, Andras Kemeny
Abstract
This paper deals with motion control for an 8-degree-of-freedom (DOF) high performance driving simulator. We formulate a constrained optimal control that defines the dynamical behavior of the system. Furthermore, the paper brings together various methodologies for addressing feasibility issues arising in implicit model predictive control-based motion cueing algorithms. The implementation of different techniques is described and discussed subsequently. Several simulations are carried out in the simulator platform. It is observed that the only technique that can provide ensured closed-loop stability by assuring feasibility over all prediction horizons is a braking law that basically saturates the control inputs in the constrained form.
BibTeX
@inproceedings{icra2019_feasibilityanaly,
title = {Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm},
author = {Carolina Rengifo and Jean-Rémy Chardonnet and Hakim Mohellebi and Damien Paillot and Andras Kemeny},
booktitle = {ICRA 2019},
year = {2019}
}