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Record W2160684217 · doi:10.1109/tac.2010.2101670

When is the Achievable Discrete-Time Delay Margin Nonzero?

2010· article· en· W2160684217 on OpenAlexaff
Darrell L. Gaudette, Daniel E. Miller

Bibliographic record

VenueIEEE Transactions on Automatic Control · 2010
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsControl theory (sociology)Discrete time and continuous timeController (irrigation)Margin (machine learning)MathematicsZero (linguistics)Stability (learning theory)LTI system theoryPole–zero plotComputer scienceControl (management)Linear systemTransfer functionEngineeringMathematical analysisStatistics

Abstract

fetched live from OpenAlex

This technical note considers the delay margin problem for discrete-time finite dimensional linear time-invariant (FDLTI) single-input single-output (SISO) systems. This problem has been studied extensively in continuous time - it is well-known that, given a FDLTI plant and controller forming a strictly proper stable feedback connection, closed loop stability will be maintained for small delays; hence the achievable delay margin using FDLTI control is strictly greater than zero. In this work, we show that this is not the case for discrete-time systems; indeed, we show that a FDLTI SISO discrete-time plant has an achievable delay margin strictly greater than zero if and only if it has no negative real unstable poles.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.005
GPT teacher head0.200
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; both teacher heads agree on what is shown here.

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

Citations10
Published2010
Admission routes1
Has abstractyes

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