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Record W2054768987 · doi:10.1109/cdc.2014.7039553

Event-based controller design for a class of nolinear systems via convex optimization

2014· article· en· W2054768987 on OpenAlexaff
Seyed Hossein Mousavi, Horacio J. Marquez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLipschitz continuityConvex optimizationController (irrigation)Control theory (sociology)Nonlinear systemEvent (particle physics)Class (philosophy)Computer scienceGenerator (circuit theory)Regular polygonOptimization problemScheme (mathematics)Mathematical optimizationMathematicsControl (management)Power (physics)Artificial intelligence

Abstract

fetched live from OpenAlex

In this paper, an event-based controller design scheme is proposed for a class of Lipschitz nonlinear systems. Using a delay system approach, the event-based system is modelled in a continuous time form. Then, the controller and event generator design methodology is formulated as a convex multi-objective optimization problem with LMI constraints, where the admissible Lipschitz constant of the system is maximized and data communication between plant and controller is minimized simultaneously. Finally, the proposed system is evaluated via simulations.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.207
Teacher spread0.194 · 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.

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

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

Citations4
Published2014
Admission routes1
Has abstractyes

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