MétaCan
Menu
Back to cohort
Record W1964887337 · doi:10.1002/asjc.84

<i>H</i><sub>∞</sub> fuzzy static output feedback control of T‐S fuzzy systems based on fuzzy Lyapunov approach

2009· article· en· W1964887337 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

VenueAsian Journal of Control · 2009
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsLakehead University
Fundersnot available
KeywordsControl theory (sociology)Fuzzy logicFuzzy control systemLyapunov functionMathematicsSet (abstract data type)Computer scienceControl (management)Nonlinear systemArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This paper is concerned with the problem of H ∞ fuzzy static output feedback control for discrete‐time Takagi‐Sugeno (T‐S) fuzzy systems, and new design methods are presented. By defining a fuzzy Lyapunov function, a new sufficient condition guaranteeing the H ∞ performance of the T‐S fuzzy systems is derived, and the condition is expressed by a set of linear matrix inequalities. In comparison with the existing literature, the proposed approach may provide more relaxed condition while ensuring better H ∞ performance. The simulation results illustrate the effectiveness of the proposed approach. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.193
Teacher spread0.185 · 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