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Record W2099852575 · doi:10.1109/ccece.1999.804873

Real-time implementation of multiple feedback loop control for a permanent magnet synchronous motor drive

2003· article· en· W2099852575 on OpenAlexaff
Saad Muftah Zeid, T.S. Radwan, M.A. Rahman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsControl theory (sociology)Robustness (evolution)Digital signal processorReference frameDigital signal processingComputer sciencePermanent magnet synchronous motorSynchronous motorCurrent loopElectronic speed controlControl engineeringDigital controlFrame (networking)MagnetEngineeringElectronic engineeringControl (management)Computer hardwareCurrent (fluid)Electrical engineering

Abstract

fetched live from OpenAlex

Permanent magnet synchronous motor drives are widely used in high performance applications. In these applications, the drive speed should fellow accurately a certain command trajectory and recover from sudden load disturbances very quickly. The systematic design procedures for both speed and current controllers have been presented. A speed controller using a synchronous reference frame PI regulator is employed as an outer loop. Moreover, two synchronous frame PI regulators are employed as inner loops to control the direct and quadrature axis current components of the motor. The complete drive has been implemented in real-time using digital signal processor (DSP) board DS-1102. The performance of the drive has been investigated by simulation as well as experimental results. The results have proved the superior performance and robustness of the proposed controllers.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.772

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)0.0010.000

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 head0.221
Teacher spread0.215 · 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

Citations3
Published2003
Admission routes1
Has abstractyes

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