MétaCan
Menu
Back to cohort
Record W2065490343 · doi:10.1109/iecon.2010.5675225

LQR with integral action controller applied to a three-phase three-switch three-level AC/DC converter

2010· article· en· W2065490343 on OpenAlexafffund
Roula Salim, Hadi Y. Kanaan, Kamal Al‐Haddad, Bachir Khedjar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie Supérieure
FundersCanada Research Chairs
KeywordsControl theory (sociology)Linear-quadratic regulatorController (irrigation)Total harmonic distortionLinearizationVoltage regulatorThree-phaseEngineeringVoltageTopology (electrical circuits)MathematicsOptimal controlComputer sciencePhysicsElectrical engineeringNonlinear system

Abstract

fetched live from OpenAlex

This paper presents a Linear Quadratic Regulator with Integral action (LQIR) applied to the three-phase three-switch three-level boost-type Vienna rectifier. The design of the controller is based on the small-signal model of the converter, which is developed in the dq0 rotating reference frame using the state-space averaging technique along with the linearization process. This controller is designed to regulate the DC bus voltages, ensure low THD of line currents and compensate the reactive power. While the standard linear quadratic regulator provides only proportional gains, the integral action is added to cancel the steady-state errors in the control loop. This is done by extending the state vector to include the integral of the source currents dq0 components, the overall output voltage and the DC load unbalance. The controller is tested using Matlab/Simulink, considering successively the cases of a balanced load, an unbalanced load and mains voltages disturbances. The obtained results have shown high performance compared to other control techniques applied to this same topology.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.248
Teacher spread0.217 · 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.

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

Citations16
Published2010
Admission routes2
Has abstractyes

Explore more

Same topicMultilevel Inverters and ConvertersFrench-language works237,207