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Record W2145498637 · doi:10.1109/acc.2009.5159803

Modified relay feedback test: Industrial loop tuner implementation and experiments

2009· article· en· W2145498637 on OpenAlexaff
Igor Boiko, A. Ernyes, W. Oli, Edgar C. Tamayo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Design
Canadian institutionsSyncrude (Canada)University of Calgary
Fundersnot available
KeywordsTunerPhase marginRelayPID controllerRobustness (evolution)Control theory (sociology)Parametric statisticsLoop gainFeedback loopLoop (graph theory)EngineeringComputer scienceControl engineeringElectronic engineeringAmplifierRadio frequencyOperational amplifierMathematicsControl (management)Physics

Abstract

fetched live from OpenAlex

An industrial loop tuner that uses conventional and modified relay feedback tests is presented in the paper. The modified relay feedback test is designed the way, so that the ultimate frequency in the test coincides with the phase cross-over frequency in the open-loop system having a PID controller. This allows for simple non-parametric tuning rules for PID controllers that provide the desired gain margin exactly. Robustness of non-parametric tuning is analyzed. Simulations are provided. Industrial loop tuner CLTUNE is described.

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)0.002
metaresearch head score (Gemma)0.004
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.032
GPT teacher head0.274
Teacher spread0.242 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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