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Record W2351633503

Robust Control of a Uncertain Generalized Systems Based on the LMI

2013· article· en· W2351633503 on OpenAlexaff
Wang Jua

Bibliographic record

VenueControl Engineering of China · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Algorithms and Applications
Canadian institutionsScience North
Fundersnot available
KeywordsControl theory (sociology)Linear matrix inequalityMathematicsRobust controlController (irrigation)Nonlinear systemLinear systemNorm (philosophy)Bounded functionFull state feedbackControl systemControl (management)Computer scienceMathematical optimizationEngineering
DOInot available

Abstract

fetched live from OpenAlex

The problem of robust control for complex systems that combine generalized system,bilinear system and uncertain system with time-delay were studied.Using the theory of Lyapunov stabilization,the sufficient condition of stabilization for SBS with time-delay and uncertainty,where uncertainties are norm- bounded and are varied with the time,is given based on the method of linear matrix inequality and using the way of enlargement in the set domain together.Moreover,the designed state feedback controller can make the closed- loop system stable.The related theory for robust control of SBS with uncertain time- delay lying between nonlinear and linear is solved based on LMI.The designed state feedback controller is more simple and more effective,which makes the closed- loop system to reach a steady state more quickly.The effectiveness and rationality of the theory are verified by the numerical example.Thus,the theory provide a certain theoretical basis for engineering control question.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.176
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations1
Published2013
Admission routes1
Has abstractyes

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