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Record W1518800580 · doi:10.1109/cdc.2003.1272637

Viability, the solution set, and fixed point approximation of hybrid systems

2004· article· en· W1518800580 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Control Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsKernel (algebra)Computer scienceConstraint (computer-aided design)AlgorithmMathematical optimizationSet (abstract data type)Sampling (signal processing)Hybrid algorithm (constraint satisfaction)MathematicsArtificial intelligenceConstraint satisfactionDiscrete mathematicsLocal consistencyTelecommunications

Abstract

fetched live from OpenAlex

This paper develops an approach for ensuring viability of hybrid systems under sampling. An algorithm based on the Fast Viability Kernel Algorithm for continuous-time viability is developed for hybrid systems with time independent constraint sets. The general existence of a fixed point for the algorithm is examined. The application of the algorithm to one control law class is carried out. His paper develops an approach for ensuring viability of hybrid systems under sampling. An algorithm based on the Fast Viability Kernel Algorithm for continuous-time viability is developed for hybrid systems with time independent constraint sets. The general existence of a fixed point for the algorithm is examined. The application of the algorithm to one control law class is carried out.

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.

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 categoriesnone
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 score0.506
Threshold uncertainty score0.231

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)0.0000.000

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 head0.006
GPT teacher head0.174
Teacher spread0.167 · 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