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Record W2141049965 · doi:10.1109/cca.1997.627533

Dynamics of a dual-unit articulated vehicle for path tracking control problem formulation

2002· article· en· W2141049965 on OpenAlexaff
Ahmad Hemami, Vladimir Polotski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsDual (grammatical number)Vehicle dynamicsPath (computing)Computer scienceUnit (ring theory)Control (management)Tracking (education)Computer visionArtificial intelligenceControl theory (sociology)EngineeringMathematicsAerospace engineeringArt

Abstract

fetched live from OpenAlex

The dynamics of motion of a class of vehicles consisting of two one-axle wheeled units pivoted together are developed for the formulation of the path tracking control problem. This particular type of vehicle is frequently used for ore transportation in underground mines. Steering of this vehicle is performed through changing the angle between the two units by means of an actuator. In this paper the equations governing the motion and the tracking error dynamics in terms of the system inputs, namely the traction forces on the front and rear wheels and the actuator force for changing the angle between the two units, are derived. These equations are nonlinear and highly coupled. However, it may be deduced that from what normally appears in practice and for low operational speeds some acceptable assumptions may be made based upon which the formulation of the control problem and the synthesis of a controller becomes much simpler.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2002
Admission routes1
Has abstractyes

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