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H∞ Control and Filtering Problems for Markov Jump Systems with Time Delay

2003· book-chapter· en· W76713672 on OpenAlexaff
El‐Kébir Boukas, Zi-Kuan Liu

Bibliographic record

VenueBirkhäuser Boston eBooks · 2003
Typebook-chapter
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsDisturbance (geology)Control theory (sociology)Computer scienceLTI system theoryController (irrigation)Context (archaeology)JumpInvariant (physics)Control (management)Linear systemControl engineeringEngineeringMathematicsArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

Practical systems are always subject to exogenous disturbance input which can cause performances degradations. The tools we developed are unfortunately inefficient for eliminating the effect of the disturbance. One alternative is to use the Roocontrol, which entails searching for a controller that stabilizes the system, and at the same time assures disturbance rejection at a given level. The7-l oo control problem has received considerable attention and thus numerous achievements have been reported to the literature. In the linear time-invariant context, early7-1control theory emerged as a frequency domain design technique [83].

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.836
Threshold uncertainty score1.000

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.172
Teacher spread0.162 · 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
Published2003
Admission routes1
Has abstractyes

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