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Record W7133064272

Implementation of fast transient response digital controllers for high frequency switch-mode power supplies

2008· dissertation· W7133064272 on OpenAlexfundno aff
Andrija Stupar

Bibliographic record

VenueTSpace · 2008
Typedissertation
Language
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsConvertersTransient (computer programming)Digital controlPower (physics)Transient responseController (irrigation)VoltageControl theory (sociology)Transient voltage suppressor
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this thesis is to develop implementations of digital controllers for switch mode power supplies providing fast transient response, superior to that of existing solutions, both analog and digital. The targeted applications are Point-of-Load converters supplying modern digital circuits. An on-chip implementation of a previously described continuous-time algorithm is presented. The operation of this continuous-time digital controller (CT-DC) is verified through simulations and also through experimental testing of the fabricated integrated circuit. The CT-DC is then extended to include a novel auto-tuning algorithm, which is capable of extracting power stage parameters simply by observing the CT-DC's transient performance. The operation of this algorithm is verified through simulations. Finally, a novel modified converter topology for improving heavy-to-light load transient performance, where the CT-DC offers only marginal improvement compared to existing solutions, is presented and verified experimentally.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.303
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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
Published2008
Admission routes1
Has abstractyes

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