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Record W2063554272 · doi:10.1109/tac.2014.2308609

A Class of Position Controllers for Underactuated VTOL Vehicles

2014· article· en· W2063554272 on OpenAlexaff
Ashton Roza, Manfredi Maggiore

Bibliographic record

VenueIEEE Transactions on Automatic Control · 2014
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)UnderactuationStabilizer (aeronautics)Controller (irrigation)Position (finance)CascadeAttitude controlControl engineeringProcess (computing)Class (philosophy)Inner loopBounded functionStability (learning theory)Computer scienceEngineeringControl (management)MathematicsAerospace engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This technical note proposes a unified framework for stabilizing a hover equilibrium for a class of vertical take-off and landing (VTOL) aircraft using a cascade control architecture which yields almost global stability in the absence of wind gusts. The control design process is partitioned into two decoupled parts: the design of a bounded position controller for a fully actuated point-mass particle, and the design of an attitude stabilizer. The position feedback is then used in an outer loop to provide reference signals for the inner loop attitude stabilizer. A number of sample feedbacks in the proposed controller class are presented, some of which include integral action to compensate for an unknown mass.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.225
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations74
Published2014
Admission routes1
Has abstractyes

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