MétaCan
Menu
Back to cohort
Record W2586189116 · doi:10.1109/tencon.2016.7848616

A sensorless speed estimation for indirect vector control of three-phase induction motor using Extended Kalman Filter

2016· article· en· W2586189116 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 institutionsBurnaby Hospital
Fundersnot available
KeywordsControl theory (sociology)Extended Kalman filterInduction motorRotor (electric)StatorVector controlKalman filterTransient (computer programming)Computer scienceDirect torque controlEngineeringVoltageControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

The accuracy of a sensorless indirect vector control of three-phase induction motor highly depends on a rotor flux, a rotor flux angle and a rotor speed. In this paper, an Extended Kalman Filter (EKF) is presented to accurately estimate the rotor flux, the rotor flux angle and the rotor speed using the direct measurement of the stator currents and voltages only. In spite of its complex computation, the EKF estimates and responses well during the steady and transient period since it has innate high convergence rate. The detailed algorithm for EKF is elucidated and the performance is verified via Matlab/Simulink simulation.

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 score0.778
Threshold uncertainty score0.725

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 head0.028
GPT teacher head0.263
Teacher spread0.234 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicSensorless Control of Electric MotorsFrench-language works237,207