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Record W2480374615 · doi:10.1109/sta.2015.7505198

A nonlinear control strategy for three-phase seven-level Shunt Active Power Filter

2015· article· en· W2480374615 on OpenAlexaff
Mohamed Haddad, S. Ktata, S. Rahmani, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)Active filterNonlinear systemActive power filterShunt (medical)AC powerComputer sciencePower controlPower (physics)Control (management)VoltageEngineeringPhysicsElectrical engineeringArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

A nonlinear control for a three-phase seven-level Neutral Point Clamped (NPC) inverter based Shunt Active Power Filter (SAPF) is proposed in this paper. The aim of this system is to mitigate the undesired reactive power and current harmonics created by nonlinear loads. The model of the Multilevel Shunt Active Power Filter (MSAPF) is divided into two subsystems including a Multi-Input Multi-Output (MIMO) subsystem defined by two current dynamics inner loop and a Single-Input Single-Output (SISO) subsystem defined by the DC capacitors voltage dynamic outer loop. The exact feedback linearization approach is applied to decouple the current dynamics. A proportional-integral controller is used to ensure DC bus voltage regulatio. An extensive simulation study using the “Power system Blockset” is tested to prove the viability of the nonlinear 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

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)0.0020.000

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 head0.115
GPT teacher head0.322
Teacher spread0.207 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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