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Record W2281959499 · doi:10.15866/iremos.v6i1.2311

A New State-Space Nonlinear Control Approach of a Doubly Fed Induction Motor Using Variable Gain PI and Fuzzy Logic Controllers

2013· article· en· W2281959499 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

VenueInternational Review on Modelling and Simulations (IREMOS) · 2013
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsControl theory (sociology)Decoupling (probability)Fuzzy logicInduction motorMultivariable calculusNonlinear systemState variableVector controlControl engineeringRotating reference frameEngineeringComputer scienceControl (management)PhysicsVoltageArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, the authors are interested on the field-oriented control with variable gain PI (VPGI) and fuzzy logic regulators of doubly fed Induction Motor (DFIM) fed by two PWM inverters with separate DC bus link. By introducing a new approach for decoupling the motor’s currents in a rotating (d-q) frame, based on the state space input-output decoupling method, we obtain the same transfer function (1/s) for all four decoupled currents. Thereafter and in order to improve the performances of the machine’s control, the VPGI and fuzzy logic controllers with seven subsets were used for the regulation speed. The Results obtained in Matlab/Simulink environment show well the effectiveness of the technique employed for the decoupling and the speed regulation of the machine.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.675

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 head0.038
GPT teacher head0.257
Teacher spread0.219 · 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