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Record W2027940133 · doi:10.1109/iecon.2007.4460322

A New Robust Controller for a Three-Phase Three-Level NPC Rectifier

2007· article· en· W2027940133 on OpenAlexaff
Aimé Francis Okou, Mohammed Tarbouchi, D. Bouchard, Aphi A. Amoussou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsControl theory (sociology)BacksteppingController (irrigation)Rectifier (neural networks)Robust controlOpen-loop controllerNonlinear systemSequence (biology)Computer scienceEngineeringControl engineeringControl (management)Adaptive controlPhysicsClosed loop

Abstract

fetched live from OpenAlex

This paper presents a new control strategy for a three-phase, three-level, neutral point clamped (NPC) rectifier. The controller is a combination of three sub-controllers, one for each of the d-axis, q-axis and zero-sequence components of the converter dynamic model In the proposed control strategy, the zero-sequence and the q-axis sub-controllers are inner loop controllers, whereas the d-axis sub-controller acts as an outer controller. Controller gains are selected in such a way that the zero-sequence controller is faster than the q-axis controller. Converter and AC voltage source parameters (amplitude and frequency) are assumed unknown. A robust nonlinear control law is derived from a backstepping procedure. It considerably attenuates unknown parameters effects. The advantage of the proposed design approach is its simplicity due to the fact that sub- controllers are decoupled, and gains are independently tuned. Simulation results show the effectiveness and the performance of the new robust controller.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.919

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 head0.061
GPT teacher head0.266
Teacher spread0.205 · 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
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

Citations3
Published2007
Admission routes1
Has abstractyes

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