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Record W3134665140 · doi:10.1109/ssd49366.2020.9364132

Robust Active Steering Control for Articulated Vehicle

2020· article· en· W3134665140 on OpenAlex
Kawther Osman, Jawhar Ghommam, Maarouf Saad

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)TruckController (irrigation)TrajectoryComputer scienceModular designTrailerVehicle dynamicsArticulated vehicleTorqueSign functionPosition (finance)Control engineeringEngineeringControl (management)Automotive engineeringMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper addresses the lane keeping scenario for articulated vehicles. The proposed system controls the steering angles of the truck and its trailer to follow a predetermined desired trajectory. During the path following, the truck position and the articulation angle are bounded to ensure a safe maneuver. The proposed approach is based on a modular system. The first module uses the function of barrier Lyapunov to apply constraints on the truck position and the trailer orientation. The second module denotes a Robust Integral of Sign of Error (RISE) feedback controller. The proposed controller is designed to define the appropriate steering angles for the truck and the trailer while compensating the vehicle's parameters uncertainties. To prove the efficiency of the developed approach, a comparative study with the computed torque controller is implemented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.575
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.174
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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