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Record W2092353321 · doi:10.1299/jamdsm.5.329

Web Tension and Velocity Control of Two-Span Roll-to-Roll System for Printed Electronics

2011· article· en· W2092353321 on OpenAlexaff
Thanh T. Tran, Kyung Hyun Choi, Dong-Eui Chang, Dong‐Soo Kim

Bibliographic record

VenueJournal of Advanced Mechanical Design Systems and Manufacturing · 2011
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsUniversity of Waterloo
FundersMinistry of Knowledge Economy
KeywordsBacksteppingController (irrigation)MATLABElectronicsControl theory (sociology)Nonlinear systemControl engineeringEngineeringReliability (semiconductor)Genetic algorithmControl systemComputer scienceControl (management)Adaptive controlArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

Due to the increasing demand of high accuracy in printed electronics industry at a micrometer-level, it is necessary to have a precise control scheme for web velocity and tension in the presence of disturbances. In this paper, a generalized mathematical model of non-linear control system is proposed and a systematic procedure is presented to design a backstepping controller taking the modified backstepping approach. With application of the proposed theory, a precise control algorithm is developed for a nonlinear two-span roll-to-roll web control system based on the backstepping method. The design parameters are chosen optimally by using the modified genetic algorithm. The reliability of the proposed algorithm is validated through simulations in Matlab/Simulink and real experiments

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.216
Teacher spread0.202 · 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 designBench or experimental
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

Citations19
Published2011
Admission routes1
Has abstractyes

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