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Record W2334153897 · doi:10.2514/6.2000-3944

Adaptive LQR gain sheduling applied to an experimental OHS aircraft

2000· article· en· W2334153897 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.

Bibliographic record

VenueAIAA Guidance, Navigation, and Control Conference and Exhibit · 2000
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceAutomotive engineeringAeronauticsAerospace engineeringControl theory (sociology)EngineeringArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

This paper describes the computer simulation and experimentation of a remotely controlled model aircraft under Adaptive LQR Gain Scheduled control. The unusual flight characteristics of this non-conventional aircraft demand a variable gain controller to provide good perfbrmace over the entire flight envelope. A mathematical model of the aircraft is computed using a Recursive Least Squares Parameter Estimation method. A linear quadratic optimal controller is designed using the estimated model at a particular operating condition. Several estimated models and controllers are developed at different operating conditions resulting in a gain schedule. The control system is simulated and then implemented on the remotely controlled aircraft. The overall aircraft performance drastically improved with the addition of Adaptive LQR Gain scheduled control.

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 categoriesMeta-epidemiology (narrow)
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 score0.754
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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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