Authors:
Martin Soyer, S. Olaru, Zhou Fang, Didier Wautier, Andras Kemeny
Keywords:
model predictive control, interpolation-based control, motion cueing algorithm, optimization
Abstract:
This paper deals with control design of high performance driving simulator Motion Cueing Algorithms (MCA). The highly constraint environment used by manufacturers to simulate driving experience implies a smart exploitation of the workspace and actuators in order to improve the acceleration feelings rendering to the driver. Since the two past decades, optimization-based motion cueing algorithms has been developed in this purpose, particularly, the Model Predictive Control (MPC) framework provides the handling of constraints applied to the system to find an optimal control action. However, the design of MPC-based MCA is a difficult task due to the theoretical and practical requirements such as stability and recursive feasibility guarantees. This contribution is a preliminary study of the application of a novel optimization-based control technique for MCA called InterpolationBased Control (IBC). Recently developed, IBC showed similar performance as MPC for regulation problems by decreasing the computation time. In this paper, an extension of IBC to the tracking problem is studied for motion cueing.
Soyer M.; Olaru S.; Fang Z.; Wautier D. and Kemeny A. Interpolation-Based MCA for acceleration rendering In: Proceedings of the Driving Simulation Conference 2020 Europe VR, Driving Simulation Association, Antibes, France, 2020, pp. 109-112
Download .txt file
@inproceedings{Soyer2020,
title = {Interpolation-Based MCA for acceleration rendering},
author = { Martin Soyer and S. Olaru and Zhou Fang and Didier Wautier and Andras Kemeny},
editor = {Andras Kemeny and Jean-Rémy Chardonnet and Florent Colombet},
year = {2020},
date = {2020-09-09},
booktitle = {Proceedings of the Driving Simulation Conference 2020 Europe VR},
pages = {109-112},
address = {Antibes, France},
organization = {Driving Simulation Association},
abstract = {This paper deals with control design of high performance driving simulator Motion Cueing Algorithms (MCA). The highly constraint environment used by manufacturers to simulate driving experience implies a smart exploitation of the workspace and actuators in order to improve the acceleration feelings rendering to the driver. Since the two past decades, optimization-based motion cueing algorithms has been developed in this purpose, particularly, the Model Predictive Control (MPC) framework provides the handling of constraints applied to the system to find an optimal control action. However, the design of MPC-based MCA is a difficult task due to the theoretical and practical requirements such as stability and recursive feasibility guarantees. This contribution is a preliminary study of the application of a novel optimization-based control technique for MCA called InterpolationBased Control (IBC). Recently developed, IBC showed similar performance as MPC for regulation problems by decreasing the computation time. In this paper, an extension of IBC to the tracking problem is studied for motion cueing.},
keywords = {interpolation-based control, model predictive control, motion cueing algorithm, optimization},
}
Download .bib file
TY - CONF
TI - Interpolation-Based MCA for acceleration rendering
AU - Soyer, Martin
AU - Olaru, S.
AU - Fang, Zhou
AU - Wautier, Didier
AU - Kemeny, Andras
C1 - Antibes, France
C3 - Proceedings of the Driving Simulation Conference 2020 Europe VR
DA - 2020/09/09
PY - 2020
SP - 109
EP - 112
LA - en-US
PB - Driving Simulation Association
L2 - https://proceedings.driving-simulation.org/proceeding/dsc-2020/interpolation-based-mca-for-acceleration-rendering
ER -
Download .ris file
Cite this article
Terms and Conditions for Downloading Driving Simulation Proceedings papers:
By downloading a scientific paper from proceedings.driving-simulation.org, you agree to the following terms and conditions:
- Personal Use Only:
The scientific paper provided on this website is solely for personal, educational, and non-commercial use. You may download and use the paper for your own reference and research purposes only.
- No Reproduction or Distribution:
You may not reproduce, distribute, transmit, publish, or otherwise make the paper available to any third party in any form, whether for commercial or non-commercial purposes, without the express written consent of the Driving Simulation Association.
- Copyright and Ownership:
The scientific paper is protected by copyright laws and is the intellectual property of the respective authors and publishers. All rights not expressly granted herein are reserved.
- Citation and Attribution:
If you use the scientific paper for research, presentations, or any other non-commercial purposes, you must provide appropriate citation and attribution to the original authors as per academic standards.
- No Modification:
You may not modify, alter, or adapt the content of the scientific paper in any way.
- Disclaimer:
The Driving Simulation Association makes no representations or warranties regarding the accuracy, completeness, or suitability of the scientific paper for any particular purpose. The paper is provided as-is, without any warranties, express or implied. The Driving Simulation Association reserves the right to terminate or restrict access to the scientific paper at any time and without notice.