MétaCan
Menu
Back to cohort
Record W3116575998 · doi:10.18280/jesa.530613

Design of Control System Using Online Tuning of PI Controllers for Three-Phase Active Front End Neutral Point Clamped Three-Level Converter

2020· article· en· W3116575998 on OpenAlexvenueno aff
Amit Ojha

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2020
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsnot available
Fundersnot available
KeywordsRectifier (neural networks)Control theory (sociology)Front and back endsMATLABController (irrigation)Point (geometry)Power (physics)Computer sciencePID controllerThree-phaseEnd pointControl (management)EngineeringControl engineeringPhysicsMathematicsElectrical engineeringVoltageTemperature control

Abstract

fetched live from OpenAlex

In conventional DC link AC-AC converter system, uncontrolled front end converter has inherent problem of power quality. To overcome the problem associated with uncontrolled front end converter, multilevel front end converter will be good choice for high power applications. In the paper, unity power factor control system (UPC) for active front end (AFE) neutral point clamped (NPC) 3-level converter is presented. PI controllers are used in UPC and for tuning of PI controllers it is essentially required to know the different time constants with their gains exactly for evaluating the optimized controller parameters for steady operation of the NPC rectifier. In this paper a simplified and accurate method of online tuning of PI controllers in UPC is derived and implemented for three phase AFE NPC 3-level converter. Complete design procedure for the design of control system for AFE NPC 3-level is also presented in this paper. Based on developed model, simulations are carried in MATLAB/SIMULIK environment. Experimentation results confirm the simulation results.

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)
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 score0.867
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.063
GPT teacher head0.263
Teacher spread0.200 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal Européen des Systèmes AutomatisésSame topicMultilevel Inverters and ConvertersFrench-language works237,207