MétaCan
Menu
Back to cohort

Sliding Mode Observer based FCS-MPC Control of Voltage Source Inverter

2023· article· en· W4390402070 on OpenAlexaff
Pengxiang Jing, Xibeng Zhang, Abhisek Ukil, Akshya Swain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersChinese Government ScholarshipUniversity of Auckland
KeywordsTotal harmonic distortionControl theory (sociology)MATLABObserver (physics)Computer scienceState observerModel predictive controlSliding mode controlInverterVoltageMode (computer interface)Control engineeringEngineeringControl (management)

Abstract

fetched live from OpenAlex

This paper introduces a Sliding Mode Observer (SMO) based Finite Control Set Model Predictive Control (FCSMPC) strategy. A digital model of the system, implemented in Matlab/Simulink, is utilized to verify the effectiveness of the proposed approach. The simulation results, encompassing both steady-state and dynamic analyses, are discussed and benchmarked against traditional FCS-MPC. The results highlight improved total harmonic distortion (THD) values, superior dynamic response, and more stable performance when integrating SMO into the FCS-MPC methodology.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.675

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 head0.019
GPT teacher head0.212
Teacher spread0.194 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicMultilevel Inverters and ConvertersFrench-language works237,207