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Record W2546272961 · doi:10.1109/iecon.2006.347421

Intelligent Speed Control of Interior Permanent Magnet Motor Drives

2006· article· en· W2546272961 on OpenAlexaff
Casey Butt, M.A. Rahman

Bibliographic record

VenueProceedings of the Annual Conference of the IEEE Industrial Electronics Society · 2006
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer scienceArtificial neural networkControl engineeringController (irrigation)Control theory (sociology)Electronic speed controlSet (abstract data type)Machine controlMotor driveArtificial neuronControl (management)EngineeringArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents an intelligent speed controller for the interior permanent magnet synchronous motor (IPMSM), based on a single artificial neuron (SAN). Traditional artificial neural network-based motor controllers require extensive offline training, which is both time consuming and requires extensive knowledge of motor behaviour for the specific drive system. In addition, drive behaviour is unpredictable when parameters outside the training set are encountered. The proposed drive system overcomes these limitations by requiring no offline training, is robust under varying operating parameters and is easily adaptable to various drive systems. Drive efficacy is verified in simulation as well as experimentally

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Annual Conference of the IEEE Industrial Electronics SocietySame topicSensorless Control of Electric MotorsFrench-language works237,207