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Record W2086314994 · doi:10.1115/1.2837438

On Steering Control of Commercial Three-Axle Vehicle

2008· article· en· W2086314994 on OpenAlex

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

VenueJournal of Dynamic Systems Measurement and Control · 2008
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsAxleTorque steeringAutomotive engineeringAutomobile handlingController (irrigation)Steering systemControl theory (sociology)EngineeringRange (aeronautics)StiffnessSteering linkageVehicle dynamicsComputer scienceControl (management)Steering wheelStructural engineering

Abstract

fetched live from OpenAlex

The steering control laws of commercial three-axle vehicle are studied based on the closed-loop control model of the driver-vehicle-road. The steering characteristics of the three-axle vehicle can be improved through adding the steering of rear wheels. For a series of combined roads defined as standard roads where the vehicle is tested, a new proposal to optimize the design parameters of the steering system is presented. The cornering stiffness of front, middle and rear wheels and outer disturbance are considered as uncertain parameters varying over a limited range. A new controller of model-following variable structure is constructed and used for controlling front and rear wheels steering of the actual vehicle, so that the steering characteristics of the uncertain vehicle model and nonlinear vehicle model can follow the characteristics of the reference model (nominal model), namely, the vehicle can keep the same steering characteristics as the nominal model on the different roads. Simulation results have demonstrated that the proposed method is reasonable and practicable.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.177
Teacher spread0.165 · 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