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Record W2020470626 · doi:10.1021/ie050643t

Control of a Process with Recycle:  Robustness of a Recycle Compensator

2006· article· en· W2020470626 on OpenAlexaff
Étienne Tremblay, André Desbiens, André Pomerleau

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsControl theory (sociology)Robustness (evolution)PID controllerProcess dynamicsProcess (computing)Controller (irrigation)Sensitivity (control systems)Computer scienceProcess controlWork (physics)Path (computing)Process engineeringControl engineeringControl (management)EngineeringTemperature controlChemistry

Abstract

fetched live from OpenAlex

Several studies on the dynamics of processes with recycle are reported in the literature. A complete summary of the effects of the recycle, along with a detailed analysis of the disturbances behavior when matter or energy is recycled, is presented in the first part of the paper. The control of processes with recycle is then discussed, including the benefits of adding a recycle compensator to a controller. Representing the system equations with Bode plots shows that the performance of a PI (proportional and integral) controller with a recycle compensator is usually better than the use of a PI controller alone. A systematic analysis of the sensitivity of the model demonstrates that this is true, even for important model errors in the recycle path. This work suggests that the negative result of recycle addition on the process dynamics can be overcome when the recycle effects are anticipated even though the recycle path model is not error free.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.024
GPT teacher head0.265
Teacher spread0.241 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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