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Record W2121489443 · doi:10.1109/ccece.2007.105

Performances of PI and Fuzzy-Logic Speed Control of Field-Oriented Induction Machine Drives

2007· article· en· W2121489443 on OpenAlex

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 institutionsUniversity of Alberta
Fundersnot available
KeywordsControl theory (sociology)Fuzzy logicElectronic speed controlInduction motorPID controllerController (irrigation)Control engineeringField (mathematics)Vector controlComputer scienceFuzzy control systemEngineeringControl (management)MathematicsVoltageElectrical engineeringArtificial intelligenceTemperature control

Abstract

fetched live from OpenAlex

A proportional-integral and fuzzy-logic speed controllers operating in indirect field-orientation are designed and compared experimentally in this paper, using a 2-HP 3-phase induction machine drive. The speed tracking capability of the two controllers are compared under no-load and various load conditions with different reference speeds. The performances of the drive are also evaluated under sudden electric and mechanical disturbances. Simulation and DSP experimental results on a 2HP 230 V/5.8 A Delta-connected 3-phase induction machine show that the performance of the fuzzy-logic controller is more satisfactory than that of the proportional-integral controller in a number of cases and, hence, can be a suitable candidate for high-performance industrial applications.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.302

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 head0.006
GPT teacher head0.208
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

Citations8
Published2007
Admission routes1
Has abstractyes

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