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Record W2535065621 · doi:10.1109/smart.2015.7399222

Analysis of linear and nonlinear control of a three-phase/level PWM DC-AC neutral point clamped converter

2015· article· en· W2535065621 on OpenAlexaff
Fatma Ezzahra Lahouar, Mahmoud Hamouda, Jaleleddine Ben Hadj Slama

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)Pulse-width modulationNonlinear systemFeed forwardLinearizationFeedback linearizationVoltage sourceVoltageOperating pointNonlinear controlComputer scienceEngineeringPhysicsElectronic engineeringControl (management)Control engineering

Abstract

fetched live from OpenAlex

This paper introduces two control methods for multilevel PWM voltage source power converter (VSC). The first approach consists of a traditional cascaded linear PI regulator while the second presents a fast voltage control scheme applying a nonlinear input-output feedback linearization (IOFL). The system modeling is obtained with the state space model of the VSC in order to meet a constant dc-bus voltage and keep the input power at unity. By IOFL, the system is linearized and decoupled without leading any zero dynamics, and then a feedforward law is derived to account for model error. Simulation results demonstrate the effectiveness response of the two designed issues in steady state and prove that with nonlinear structures, output signal responses become faster than those in cascaded control schemes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.259
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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