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Record W4249884895 · doi:10.1109/pesc.1990.131175

A critical assessment of the continuous-system approximate methods for the stability analysis of a sampled data system

2002· article· en· W4249884895 on OpenAlexaff
H.A. Kojori, J.D. Lavers, S.B. Dewan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)Stability (learning theory)Transfer functionPulse-width modulationController (irrigation)Computer scienceControl systemStep responseMathematicsPower (physics)EngineeringControl engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

A critical assessment of the approximate methods for the stability analysis of a PWM (pulse width modulation) static VAr (volt-ampere reactive) compensator, which is a typical sampled data power converter system. is presented. The open-loop transfer function of the system is derived and verified experimentally. The closed-loop operation of the system with a PI (proportional-integral) controller is investigated. Different continuous-system approximate models for the stability analysis of the system are developed, and their validity is investigated. In particular, it is shown that, by considering only the principal strip model and by approximating the dead time of the zero-order hold unit, approximate models are obtained which cannot accurately predict the stability region of the system. Therefore, these approximate models are not generally reliable for design purposes. A modified frequency-domain model is used to predict the stability region accurately. The dynamic performance and the closed-loop design of this sampled data system are verified with the Electromagnetic Transients Program. All the predicted results are experimentally verified on a laboratory-scale prototype PWM static VAr compensator.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.083
GPT teacher head0.375
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2002
Admission routes1
Has abstractyes

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