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Record W2480967224 · doi:10.1109/iecon.1994.398145

Adaptive nonlinear control of a permanent magnet synchronous motor

2002· article· en· W2480967224 on OpenAlexaff
L. Ben Amor, Louis‐A. Dessaint, M. Ghribi, Ouassima Akhrif

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)Decoupling (probability)Feedback linearizationNonlinear systemA priori and a posterioriAdaptive controlLinearizationTorquePermanent magnet synchronous motorVector controlComputer scienceMagnetControl engineeringControl (management)EngineeringInduction motorArtificial intelligencePhysicsVoltageElectrical engineering

Abstract

fetched live from OpenAlex

In this work an adaptive nonlinear control method is applied to a permanent magnet synchronous motor. Quadratic and direct currents decoupling and control are achieved through feedback linearization. Direct current is controlled to zero and torque becomes only proportional to the quadratic current. Also a near unity power factor is achieved. Parameters variation is compensated by using an adaptive scheme and no a priori knowledge of real parameters is required. The performance of the proposed adaptive nonlinear control scheme is demonstrated by simulation results. These results show that the proposed method achieves the same high dynamic performance as vector control.>

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.174
Teacher spread0.166 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations21
Published2002
Admission routes1
Has abstractyes

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