Back to Search Start Over

The Role of a Novel Discrete-Time MRAC Based Motion Cueing on Loss of Control at a Hexapod Driving Simulator

Authors :
Frédéric Merienne
Christophe Guillet
Andras Kemeny
Damien Paillot
Baris Aykent
Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i)
Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM)
Arts et Métiers Sciences et Technologies
HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies
HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Centre Technique de Simulation
RENAULT
Technocentre Renault [Guyancourt]
Laboratoire Electronique, Informatique et Image ( Le2i )
Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS )
Source :
Intelligent Control and Automation, Intelligent Control and Automation, 2015, 6 (1), pp.84-102. ⟨10.4236/ica.2015.61010⟩, Intelligent Control and Automation, 2015, 6 (1), pp.84-102. 〈10.4236/ica.2015.61010〉
Publication Year :
2015

Abstract

The objective of this paper is to present the advantages of Model reference adaptive control (MRAC) motion cueing algorithm against the classical motion cueing algorithm in terms of biome- chanical reactions of the participants during the critical maneuvers like chicane in driving simu- lator real-time. This study proposes a method and an experimental validation to analyze the ves- tibular and neuromuscular dynamics responses of the drivers with respect to the type of the con- trol used at the hexapod driving simulator. For each situation, the EMG (electromyography) data were registered from arm muscles of the drivers (flexor carpi radialis, brachioradialis). In addi- tion, the roll velocity perception thresholds (RVT) and roll velocities (RV) were computed from the real-time vestibular level measurements from the drivers via a motion-tracking sensor. In or- der to process the data of the EMG and RVT, Pearson’s correlation and a two-way ANOVA with a significance level of 0.05 were assigned. Moreover, the relationships of arm muscle power and roll velocity with vehicle CG (center of gravity) lateral displacement were analyzed in order to assess the agility/alertness level of the drivers as well as the vehicle loss of control characteristics with a confidence interval of 95%. The results showed that the MRAC algorithm avoided the loss of adhe- sion, loss of control (LOA, LOC) more reasonably compared to the classical motion cueing algo- rithm. According to our findings, the LOA avoidance decreased the neuromuscular-visual cues lev- el conflict with MRAC algorithm. It also revealed that the neuromuscular-vehicle dynamics conflict has influence on visuo-vestibular conflict; however, the visuo-vestibular cue conflict does not in- fluence the neuromuscular-vehicle dynamics interactions.; International audience; The objective of this paper is to present the advantages of Model reference adaptive control (MRAC) motion cueing algorithm against the classical motion cueing algorithm in terms of biome- chanical reactions of the participants during the critical maneuvers like chicane in driving simu- lator real-time. This study proposes a method and an experimental validation to analyze the ves- tibular and neuromuscular dynamics responses of the drivers with respect to the type of the con- trol used at the hexapod driving simulator. For each situation, the EMG (electromyography) data were registered from arm muscles of the drivers (flexor carpi radialis, brachioradialis). In addi- tion, the roll velocity perception thresholds (RVT) and roll velocities (RV) were computed from the real-time vestibular level measurements from the drivers via a motion-tracking sensor. In or- der to process the data of the EMG and RVT, Pearson’s correlation and a two-way ANOVA with a significance level of 0.05 were assigned. Moreover, the relationships of arm muscle power and roll velocity with vehicle CG (center of gravity) lateral displacement were analyzed in order to assess the agility/alertness level of the drivers as well as the vehicle loss of control characteristics with a confidence interval of 95%. The results showed that the MRAC algorithm avoided the loss of adhe- sion, loss of control (LOA, LOC) more reasonably compared to the classical motion cueing algo- rithm. According to our findings, the LOA avoidance decreased the neuromuscular-visual cues lev- el conflict with MRAC algorithm. It also revealed that the neuromuscular-vehicle dynamics conflict has influence on visuo-vestibular conflict; however, the visuo-vestibular cue conflict does not in- fluence the neuromuscular-vehicle dynamics interactions.

Subjects

Subjects :
[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]
[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]
0209 industrial biotechnology
Engineering
Adaptive control
02 engineering and technology
Electromyography
Modélisation et simulation [Informatique]
Motion (physics)
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
020901 industrial engineering & automation
0302 clinical medicine
EMG Analysis
Automatique [Informatique]
Robotique [Informatique]
[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering
[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]
Driving Simulator
[ INFO.INFO-ES ] Computer Science [cs]/Embedded Systems
Head Dynamics
Vestibular system
medicine.diagnostic_test
[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]
Driving simulator
[SPI.MECA.BIOM]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph]
Optimisation et contrôle [Mathématique]
Automatique / Robotique [Sciences de l'ingénieur]
[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]
Center of gravity
[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]
Interface homme-machine [Informatique]
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems
[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
[ SPI.MECA.BIOM ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph]
[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation
Base de données [Informatique]
Model Reference Adaptive Control
[SPI.AUTO]Engineering Sciences [physics]/Automatic
03 medical and health sciences
Intelligence artificielle [Informatique]
Mécanique: Génie mécanique [Sciences de l'ingénieur]
[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC]
Control theory
[ SPI.AUTO ] Engineering Sciences [physics]/Automatic
[ INFO.INFO-PL ] Computer Science [cs]/Programming Languages [cs.PL]
[ INFO.INFO-AU ] Computer Science [cs]/Automatic Control Engineering
medicine
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]
[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]
Simulation
Mécanique: Biomécanique [Sciences de l'ingénieur]
Hexapod
Discrete-Time Control
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]
[INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL]
Systèmes embarqués [Informatique]
business.industry
Loss of Control
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Alertness
business
030217 neurology & neurosurgery
Langage de programmation [Informatique]

Details

Language :
English
Database :
OpenAIRE
Journal :
Intelligent Control and Automation, Intelligent Control and Automation, 2015, 6 (1), pp.84-102. ⟨10.4236/ica.2015.61010⟩, Intelligent Control and Automation, 2015, 6 (1), pp.84-102. 〈10.4236/ica.2015.61010〉
Accession number :
edsair.doi.dedup.....f6ef88c09f9c2c13567876a4f1557cba
Full Text :
https://doi.org/10.4236/ica.2015.61010⟩