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Record W2051297182 · doi:10.1109/cdc.2013.6760341

Strong stabilization of piezoelectric beams with magnetic effects

2013· article· en· W2051297182 on OpenAlexaff
Kirsten Morris, Ahmet Özer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStability and Controllability of Differential Equations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsControl theory (sociology)PiezoelectricityHamiltonian (control theory)Beam (structure)Boundary value problemMagnetic bearingController (irrigation)PhysicsDifferential equationComputer scienceMathematicsAcousticsControl (management)Mathematical optimizationMagnet

Abstract

fetched live from OpenAlex

It is widely accepted in the literature that magnetic effects in the piezoelectric beams is relatively small, and does not change the overall dynamics. Therefore, most models for piezoelectric beams completely ignore the magnetic energy. These models are known to be exponentially stabilizable by a mechanical feedback controller in the energy space. In this paper, we use a variational approach to derive the differential equations and boundary conditions that model a single piezoelectric beam with magnetic effects. Next, we show that the resulting control system can be formulated as a port-Hamiltonian system and is hence well-posed. Finally, by using only an electrical feedback controller (the current flowing through the electrodes), we show that the closed-loop system is strongly stable in the energy space for a dense set of system parameters. The difference between this result and that for models that neglect magnetic effects is discussed.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.004
GPT teacher head0.168
Teacher spread0.164 · 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 designTheoretical or conceptual
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

Citations59
Published2013
Admission routes1
Has abstractyes

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