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Record W2039197659 · doi:10.1115/1.2196419

A Problem With the LQ Control of Overhead Cranes

2004· article· en· W2039197659 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 · 2004
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsPayload (computing)Overhead (engineering)Control theory (sociology)Control (management)Mathematical optimizationComputer scienceOverhead craneStability (learning theory)Optimal controlQuadratic equationMathematicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The control of an overhead crane is a classic optimum control problem, and its solution can be found in most textbooks on the subject of automatic controls. However, there is a design issue with respect to the relative mass of the cart and the suspended payload. If this problem is ignored, then the results of an analysis can be misleading and the response can be unstable. Based on a stability analysis, a design recommendation for optimal asymptotic linear quadratic (LQ) controllers with fixed gains is presented to avoid this problem. The results are validated by both simulation and experiment.

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)0.002
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 score0.790
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.005
GPT teacher head0.165
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