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Record W2105614501 · doi:10.1109/tcst.2003.810377

Servomechanism controller design of web handling systems

2003· article· en· W2105614501 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

VenueIEEE Transactions on Control Systems Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsServomechanismControl theory (sociology)Control engineeringController (irrigation)Control systemMultivariable calculusEngineeringProcess controlAutomatic controlProcess (computing)Computer scienceControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

In traditional web handling processes, web tension and speed are typically controlled assuming that the web system consists of a number of single-input-single-output systems. This assumption often results in large interactions occurring in the closed-loop system between the control loops and, hence, results in high-quality control being difficult to achieve. In this paper, the control of the web handling processes is treated as a multivariable servomechanism problem. Two types of controller design, the "perfect control servomechanism controller" and the "tuning regulator", are studied and implemented on an industrial web machine. The experimental results obtained show that these controllers provide excellent tension and speed response compared with conventional controllers used in web systems. In particular, it is shown that the "tuning regulator" approach is only marginally worse than the "perfect control servomechanism controller" approach, despite the fact that it does not require a mathematical model of the web process, and is simpler to implement.

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 categoriesMeta-epidemiology (narrow)
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 score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.196
Teacher spread0.187 · 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