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Record W2108139825 · doi:10.1109/icca.2003.1595011

Robust Flight Control Design with Handling Qualities Incorporation via Low Order Model Matching

2003· article· en· W2108139825 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl Systems and Identification
Canadian institutionsPolytechnique MontréalÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaBombardierFlorida State University
KeywordsParametric statisticsLinear fractional transformationCenter of gravityRobust controlActuatorAerospaceController (irrigation)Control theory (sociology)Parametric modelMatching (statistics)Computer scienceEngineeringControl engineeringControl systemControl (management)Aerospace engineeringMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a robust pitch rate control design for longitudinal aircraft motion based on μ-synthesis is presented. A Linear Fractional Transformation (LFT) uncertainty model is first derived for robust synthesis. The uncertainty dealt with is of parametric nature and represents the variations of weight and center of gravity in the aircraft models. A controller is then developed and tested on the full longitudinal model of the Challenger 604 aircraft provided by Bombardier Aerospace Inc. The model includes both short-period and phugoïd modes of the aircraft, the stick, the actuator and the sensors. It is shown that the controller guarantees desired performance with predicted Level 1 handling qualities under varying weight and center of gravity locations.

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.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.443

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 head0.020
GPT teacher head0.183
Teacher spread0.162 · 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

Quick stats

Citations1
Published2003
Admission routes2
Has abstractyes

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