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Damien Paillot

dblp:172/3471 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control
model predictive control
0.412019
Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm · ICRA 2019
Robotics › Motion planning and robot control › robot control
motion control
0.412019
Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm · ICRA 2019
Robotics › Motion planning and robot control › robot control › optimal control
constrained optimal control
0.112019
Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm · ICRA 2019

Methods — techniques the papers use, named apart from their topics

model predictive control · 0.4constrained optimal control · 0.4braking law · 0.4
YearPublicationVenuePosition
2019 Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm
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.
Carolina Rengifo, Jean-Rémy Chardonnet, Hakim Mohellebi, Damien Paillot, Andras Kemeny
ICRA4