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Record W1540794476

Compensation of hysteresis nonlinearity for a piezoelectric actuator using a stop operator-based Prandtl-Ishlinskii model

2011· article· en· W1540794476 on OpenAlexaff
Zhi Li, Omar Aljanaideh, Chun‐Yi Su, Subhash Rakheja, Mohammad Al Janaideh

Bibliographic record

VenueInternational Conference on Advanced Mechatronic Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)Feed forwardHysteresisActuatorCompensation (psychology)Nonlinear systemPrandtl numberPiezoelectricityTracking (education)Computer scienceEngineeringControl engineeringPhysicsAcousticsControl (management)MechanicsConvectionArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Piezoelectric actuators exhibit limited tracking performance in precision control due to their inherent hysteresis nonlinearity. In this paper, the hysteresis behavior is described by a play operator-based Prandtl-Ishlinskii (PPI) model. And a corresponding stop operator-based Prandtl-Ishlinskii (SPI) model is utilized as a feedforward compensator for canceling the hysteresis effect in piezoelectric actuators. For this purpose, the two parameters describing the SPI model, the thresholds and the weights, are analytically derived from the PPI model, which constitutes a main contribution of the paper. As an illustration, the effectiveness of the compensator is demonstrated through simulation and experimental results attained with a piezoelectric micro-positioning stage. Both the simulation and experimental results show that the SPI model can serve as an effective feedforward hysteresis compensator and can thus enhance the tracking/positioning precision of the piezoelectric actuators.

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)0.000
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 score0.833
Threshold uncertainty score1.000

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 communication0.0000.000
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 head0.076
GPT teacher head0.279
Teacher spread0.203 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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