MétaCan
Menu
Back to cohort
Record W2144939320 · doi:10.1109/isie.2000.930387

Model reference adaptive fuzzy controller for induction motor using auto-attentive approach

2002· article· en· W2144939320 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 institutionsRoyal Military College of Canada
Fundersnot available
KeywordsControl theory (sociology)Induction motorComputer scienceController (irrigation)Fuzzy logicControl engineeringOpen-loop controllerAdaptive controlFuzzy control systemComputationArtificial intelligenceEngineeringAlgorithmVoltageControl (management)

Abstract

fetched live from OpenAlex

This paper presents a model reference adaptive fuzzy speed controller for induction motor using the auto-attentive approach. It consists of developing an adaptive controller that can track the change of the operating point and the plant parameters even in magnetic saturation mode. The adaptive mechanism should be fast enough for all the tracking process. The proposed approach helps to increase the accuracy of the controller around the set point and keep the number of the roles in the rule-base as low as possible. This would minimize the computation complexity and enhance the system performance.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score0.930

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 head0.097
GPT teacher head0.235
Teacher spread0.138 · 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
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicSensorless Control of Electric MotorsFrench-language works237,207