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Record W7132964440

Synchronization to disturbed AC utility network signals in power electronics applications

2002· dissertation· W7132964440 on OpenAlexfundno aff
Stjepan Pavljašević

Bibliographic record

VenueTSpace · 2002
Typedissertation
Language
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsSIGNAL (programming language)Synchronization (alternating current)Transfer functionNoise (video)Signal transfer functionOversamplingFilter (signal processing)Anti-aliasing filterDigital signalControl theory (sociology)
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a digital signal processing system for synchronization to AC utility network signals in power electronics applications. The proposed system is suitable in applications where the signal to which synchronization must be accomplished contains severe disturbances and where the signal frequency and the signal amplitude are variable. The system is based on a multirate phase-locked loop (PLL). The main advantages of the multirate approach are that it relaxes the implementation of the antialiasing filter and it enables one to accommodate the varying amplitude of the input signals. The antialiasing filter, which is in this case a high order bandpass filter, is implemented in the digital part of the system. This feature is achieved by applying the oversampling technique to the input signal. The antialiasing filter automatically adapts to the input signal frequency through the system's variable sample rate operation. The thesis deals with modeling, analysis, control and implementation issues of the proposed system. Nonlinear and linear state-space models and a transfer function model of the system are derived. The system's control aspects are discussed using the derived transfer function model. The system is implemented on a platform based on the Texas Instruments TMS320C31 floating point digital signal processor. Tracking properties of the implemented system are verified with realistic signals such as a sinusoidal signal containing notch type disturbance and noise and an arc furnace voltage signal.

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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.280
Teacher spread0.270 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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