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Record W2139712300 · doi:10.1109/ccece.2004.1347671

Real time flux and torque estimator for induction machines

2004· article· en· W2139712300 on OpenAlex
M. Zerbo, A. Ba-Razzouk, Pierre Sicard

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsControl theory (sociology)StatorEstimatorTorqueDirect torque controlRotor (electric)Vector controlFlux (metallurgy)Induction motorPosition (finance)Computer scienceVoltageEngineeringMathematicsPhysicsElectrical engineeringArtificial intelligenceMaterials scienceStatistics

Abstract

fetched live from OpenAlex

This paper presents a novel method for flux and torque estimation. Based on the observation and analysis of the behaviour of the classical torque and flux estimator structure in an indirect rotor flux oriented control (IRFOC) of a voltage fed squirrel cage asynchronous machine, the proposed structure is fully independent of the stator resistance. Implemented in dq coordinates, the estimator is based on simple calculus of signal averages. Only stator voltages and currents are required for the estimation, along with maximum and minimum detectors. Flux position and magnitude are estimated separately, and dq fluxes are rebuilt for torque estimation. The estimator is designed for systems running above 0.5 Hz, making it available for induction machine (IM) applications running over a wide range of speed. Simulations are performed on SimPowerSystems.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.005
GPT teacher head0.207
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

Quick stats

Citations4
Published2004
Admission routes1
Has abstractyes

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