TR2019-063
Steering of Autonomous Vehicles Based on Friction-Adaptive Nonlinear Model-Predictive Control
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- "Steering of Autonomous Vehicles Based on Friction-Adaptive Nonlinear Model-Predictive Control", American Control Conference (ACC), DOI: 10.23919/ACC.2019.8814448, July 2019, pp. 965-970.BibTeX TR2019-063 PDF
- @inproceedings{Berntorp2019jul3,
- author = {Berntorp, Karl and Quirynen, Rien and Di Cairano, Stefano},
- title = {Steering of Autonomous Vehicles Based on Friction-Adaptive Nonlinear Model-Predictive Control},
- booktitle = {American Control Conference (ACC)},
- year = 2019,
- pages = {965--970},
- month = jul,
- publisher = {IEEE},
- doi = {10.23919/ACC.2019.8814448},
- url = {https://www.merl.com/publications/TR2019-063}
- }
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- "Steering of Autonomous Vehicles Based on Friction-Adaptive Nonlinear Model-Predictive Control", American Control Conference (ACC), DOI: 10.23919/ACC.2019.8814448, July 2019, pp. 965-970.
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MERL Contact:
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Research Areas:
Abstract:
The vehicle steering-control behavior is highly dependent on the road surface. However, the road surface conditions are typically unknown a priori, and control actions that are safe to perform on asphalt may therefore lead to vehicle instability on low-friction surfaces. It is therefore important that the road surface is estimated, or at least detected, online, and that the vehicle dynamics control algorithms are adapted to the changing conditions. In this paper, we propose a nonlinear model-predictive control (NMPC) scheme that adapts its tire parameters in response to the estimated road surface. We show how estimating the initial slope of the tire-force curve can be used to change the full nonlinear tire-curve used by the NMPC and validate the method in simulation.
Related News & Events
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NEWS MERL researchers presented 8 papers at American Control Conference Date: July 10, 2019 - July 12, 2019
Where: Philadelphia
MERL Contacts: Mouhacine Benosman; Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, OptimizationBrief- At the American Control Conference, MERL presented 8 papers on subjects including model predictive control applications, estimation and motion planning for vehicles, modular control architectures, and adaptation and learning.