MétaCan
Menu
Back to cohort
Record W2369519998

A New Stabilization Conditions for T-S Fuzzy Descriptor System

2013· article· en· W2369519998 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

VenueControl Engineering of China · 2013
Typearticle
Languageen
FieldComputer Science
TopicCybersecurity and Information Systems
Canadian institutionsScience North
Fundersnot available
KeywordsMathematicsControl theory (sociology)Fuzzy control systemFuzzy logicStability (learning theory)Nonlinear systemTime derivativeMembership functionDerivative (finance)Exponential stabilityMathematical optimizationApplied mathematicsControl (management)Computer scienceArtificial intelligenceMathematical analysisMachine learning
DOInot available

Abstract

fetched live from OpenAlex

Fuzzy-model-based(FMB)control approach offered a systematic ways to tackle nonlinear systems.At the same time,For continuous- time T-S fuzzy systems,a certain degree of conservativeness remains because information on the time derivative of membership functions is generated into the fuzzy Lyapunov function(FLF) time-derivative.In this paper,we investigated the problems of stability analysis of continuous- time T-S fuzzy descriptor systems based on the descriptor system approach.New criteria for the asymptotic stability of the T-S fuzzy descriptor systems are established.Moreover,with the usage of the non-PDC control scheme,less conservative stabilizations are attained by both introducing additional variables and applying a kind of relaxed technique.Furthermore,all the conditions we obtained are expressed in the terms of linear matrix inequalities.And numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed conditions.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.332

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 communication0.0000.001
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 head0.005
GPT teacher head0.179
Teacher spread0.174 · 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