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Record W2121044717 · doi:10.1109/pesc.2007.4342153

LQR with Integral Action to Enhance Dynamic Performance of Three-Phase Three-Wire Shunt Active Filter

2007· article· en· W2121044717 on OpenAlexaff
Bachir Kedjar, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)Total harmonic distortionHarmonicsLinear-quadratic regulatorAC powerPower factorEngineeringActive filterThree-phaseVoltageComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents the design of a Linear Quadratic Regulator (LQR) with Integral action (LQIR) to improve dynamic performance of a three-phase three-wire shunt active power filter (SAF). The integral action is added to cancel the steady state errors knowing that the standard LQR provides only proportional gains. The controller is designed to achieve DC bus voltage regulation, harmonics and reactive power compensation. The converter model is set in the dq rotating reference frame augmented with the integral of q component of the SAF currents and DC bus voltage. The performance of the controller depends on the weightening matrix which is chosen to guaranty satisfactory responses. The converter is controlled as a whole and a fixed PWM at 2.34 kHz is used to generate the gating signals of the power devices. The system is tested for both active and reactive power variations of the combined linear and non-linear load, for a distorted/unbalanced voltage source, and for unbalanced loads. The Simulation results obtained show good performance in terms of the DC bus voltage regulation (small overshoot and very fast time response) and low total harmonic distortion (THD) of ac line currents.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.512

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 head0.022
GPT teacher head0.298
Teacher spread0.276 · 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 designBench or experimental
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

Citations8
Published2007
Admission routes1
Has abstractyes

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