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Record W2117161952 · doi:10.1109/epec.2009.5420896

Robust continuous generalized predictive control of a permanent magnet synchronous motor drive

2009· article· en· W2117161952 on OpenAlexaff
Rachid Errouissi, Mohand Ouhrouche

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsControl theory (sociology)DSPACEPermanent magnet synchronous motorSynchronous motorTorqueModel predictive controlController (irrigation)Computer scienceControl engineeringObserver (physics)Robust controlMachine controlMagnetTracking errorEngineeringControl systemControl (management)PhysicsArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

A robust generalized predictive controller (GPC) with a disturbance observer for a permanent magnet synchronous motor (PMSM) is presented. The proposed GPC controller combines the linear predictive control techniques together with the disturbance observer, which is designed to take into account the load torque variations and uncertain electrical and mechanical parameters. Stability of the closed-loop system is guaranteed and the controller is easy to implement. The system performance is tested with an experimental setup consisting of a PMSM and dSPACE DS1104 Board. A good speed tracking performance with no error is obtained while the d-axis current regulation is satisfactorily guaranteed.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.182
Teacher spread0.175 · 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 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

Citations2
Published2009
Admission routes1
Has abstractyes

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