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Deterministic Time Delay Systems

2002· book-chapter· en· W58253391 on OpenAlexaff
El‐Kébir Boukas, Zi-Kuan Liu

Bibliographic record

VenueBirkhäuser Boston eBooks · 2002
Typebook-chapter
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsControl theory (sociology)Class (philosophy)Robustness (evolution)Dynamical systems theoryComputer scienceNorm (philosophy)Bounded functionStability (learning theory)MathematicsControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

It is clear from the examples given previously that the the investigation of the class of dynamical time delay systems is of great importance in dealing with the world economy. It is why much attention has been paid to this class of systems by many researchers from different communities. During recent decades, the control community has contributed to many problems of this class of systems. Part I focuses on this class of systems and gives a summary of what has been done in the area. It addresses mainly the problems of stability and stabilizability of the class of linear systems with time delay. It also deals with the robustness of stability and stabilizability when uncertainties are assumed to be of the norm-bounded type. Memoryless and memory state feedback controllers and output feedback controllers are used to stabilize dynamical time delay systems and to ensure the desired performance.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.739
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.016
GPT teacher head0.179
Teacher spread0.163 · 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 designNot applicable
Domainnot available
GenreOther

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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