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Record W1974803801 · doi:10.2514/6.2015-1256

New methodology for the controller of an electrical actuator for morphing a wing

2015· article· en· W1974803801 on OpenAlexafffund
Michel Joël Tchatchueng Kammegne, Sheheryar Khan, Ruxandra Mihaela Botez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsÉcole de Technologie Supérieure
FundersConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsMorphingActuatorWingComputer sciencePneumatic actuatorControl engineeringAerospace engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The modeling, simulation and control of an electrical actuator used for morphing wing are presented. Because of its small size, this actuator belongs to the category of miniature actuators. Before proceeding with the modeling, the actuator was tested experimentally to ensure that the entire range of the requirements (rated or nominal torque, nominal current, nominal speed, static force, size) would be fulfilled. The complete electromechanical energy miniature actuator was designed in-house, as there is no actuator on the market that could fit directly inside the wing model. The wing model is a portion of an existing regional aircraft. The miniature electrical actuator consists of a brushless direct current (BLDC) motor with a gearbox and a screw for pushing and pulling the flexible upper surface of the wing. The electrical motor and the screw are coupled through a gearing system. The first part of the paper gives a literature review of the actuators used for morphing wing. The theoretical analysis of the BLDC motor and its gearbox are presented in the second part. The design of both controllers (a current and a positioning controller) used to improve the dynamic behavior of the actuator are presented in the third part. The experimental results of the numerical analysis will be presented in a subsequent paper. The numerical analysis is done with MATLAB/SIMULINK, and a Digital Signal Processor (DSP) will be used for experimental evaluation.

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)0.001
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 score0.746
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.108
GPT teacher head0.313
Teacher spread0.205 · 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
Published2015
Admission routes2
Has abstractyes

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