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Record W2910394073 · doi:10.1109/epec.2018.8598392

Controller Implementation and Performance Evaluation of a High Power Three-Phase Active Power Filter using Controller Hardware-in-the-Loop Simulation

2018· article· en· W2910394073 on OpenAlexaff
Hang Li, A.M. Gole, Carl Ngai Man Ho

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPower factorController (irrigation)Digital signal processorDigital signal processingHardware-in-the-loop simulationControl theory (sociology)Open-loop controllerComputer scienceDigital controlAC powerActive filterEngineeringElectronic engineeringVoltageControl engineeringEmbedded systemElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper presents a demonstration of Real-Time High-Speed Controller Hardware-in-the-Loop (CHIL) testing for a DSP-based controller of a Shunt Active Power Filter (APF) for medium voltage (MV) grid power quality improvements. A Real-Time simulator (RT Box) and a Digital Signal Processor (DSP) are used for the CHIL simulation to validate the control algorithms which are implemented in a commercial low-cost DSP. Two control loops have been used in the control system. The filter reference current is extracted based on synchronous reference frame. Hysteresis current control is employed as the inner control loop for generating switching signals. The DC side capacitor voltage of the APF is maintained by a PI controller. The results show the APF associated with the implemented controller can mitigate variety power quality problems, such as harmonic elimination, power factor correction, and load balancing. The whole CHIL simulation system work stable with high switching frequency.

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)0.001
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: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.033
GPT teacher head0.333
Teacher spread0.300 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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