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Record W2086603338 · doi:10.1109/ias.2014.6978395

Online loss minimization based adaptive flux observer for direct torque and flux control of PMSM drive

2014· article· en· W2086603338 on OpenAlexaff
M. Nasir Uddin, HonBin Zou, F. Azevedo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsLakehead University
Fundersnot available
KeywordsControl theory (sociology)Vector controlObserver (physics)TorqueDirect torque controlMinificationMRASMagnetic fluxPermanent magnet synchronous motorEngineeringSynchronous motorControl engineeringMachine controlComputer scienceInduction motorControl (management)MagnetMagnetic fieldPhysicsVoltageElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a novel adaptive flux observer based direct torque and flux control (DTFC) of permanent magnet synchronous motor (PMSM) drive. An online loss minimization algorithm (LMA) is developed to estimate the airgap flux so that the motor operates at minimum loss condition while taking the general advantages of DTFC scheme over conventional vector control scheme. The proposed DTFC based PMSM drive incorporating the LMA based flux observer is implemented in real-time using the DSP board DS1104 for a laboratory 5 hp motor. The performance of the proposed LMA based DTFC control of PMSM drive is tested in both simulation and experiment at different operating conditions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score0.661

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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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 designSimulation or modeling
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

Citations11
Published2014
Admission routes1
Has abstractyes

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