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Record W2049836006 · doi:10.1088/0964-1726/24/4/045001

Output feedback integral control for nano-positioning using piezoelectric actuators

2015· article· en· W2049836006 on OpenAlexaff
Jinjun Shan, Liu Yang, Zhan Li

Bibliographic record

VenueSmart Materials and Structures · 2015
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsYork University
FundersNational Natural Science Foundation of China
KeywordsPiezoelectricityActuatorNano-Control theory (sociology)Materials scienceControl (management)EngineeringComputer scienceComposite materialElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper proposes a robust output feedback controller for a piezoelectrically actuated system with only position sensor. This considered piezoelectric actuator (PEA) system is subjected to model imperfection, creep nonlinearity, hysteresis nonlinearity and other external effects. The designed controller employs a second-order auxiliary system and a discontinuous uncertainty and disturbance estimation term to generate filtered error signals and to compensate for the model uncertainties and system disturbance, respectively. The global stability of the proposed controller is proved through Lyapunov-based stability analysis. The feasibility and effectiveness of the proposed control approach are verified experimentally using a PEA stage. Results demonstrate that both set-point and tracking control without/with external loads are realized with good performance and the PEA system with high-accuracy can be achieved. Moreover, the robustness of the controller is verified and analyzed through the sinusoidal tracking with external disturbance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.851

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 head0.013
GPT teacher head0.216
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.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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