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Record W2054831196 · doi:10.1109/tcst.2011.2178415

Design and Experimental Validation of a Nonlinear Low-Level Controller for an Unmanned Fin-Less Airship

2012· article· en· W2054831196 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

VenueIEEE Transactions on Control Systems Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsControl theory (sociology)Controller (irrigation)BacksteppingFlight testAttitude controlEngineeringFinDescent (aeronautics)Nonlinear systemFlight dynamicsVehicle dynamicsControl engineeringComputer scienceSimulationAerodynamicsAerospace engineeringAdaptive controlControl (management)

Abstract

fetched live from OpenAlex

This paper discusses the design of a combined backstepping/Lyapunov controller for the attitude, velocity and height control of an unmanned, unstable, fin-less airship. As the airship actuation has more degrees of freedom than the motion controlled, the controller includes a quadratic optimization algorithm to find the optimal thruster commands. The control law developed provides attitude and velocity control for the entire airship flight regime, i.e., hover, vertical ascent and descent as well as cruise, all with a single controller. Controller performance is first verified using a simulation that includes detailed modeling of sensor noise, computational delays and actuation dynamics. Subsequently, the controller is tested in outdoor flight tests. The controller has been found to perform well both in simulation and flight tests. The controller parameters were identical in simulation and flight test demonstrating the high fidelity of the simulation.

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: Empirical · Consensus signal: none
Teacher disagreement score0.758
Threshold uncertainty score0.984

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 head0.027
GPT teacher head0.234
Teacher spread0.207 · 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