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Record W2159549489 · doi:10.2514/6.2010-945

Adaptive Sliding Mode Fault Tolerant Control of Civil Aircraft with Separated Uncertainties

2010· article· en· W2159549489 on OpenAlex
Tao Wang, Wenfang Xie, Youmin Zhang

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

Venue48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition · 2010
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFault toleranceControl theory (sociology)Mode (computer interface)Control (management)Sliding mode controlComputer scienceControl engineeringEngineeringPhysicsArtificial intelligenceDistributed computing

Abstract

fetched live from OpenAlex

In this paper, a sliding mode control algorithm is developed to synthesize nonlinear control system for aircraft systems with actuator faults. Two design parameters are used to deal with uncertainty caused by actuator faults and uncertainty in system dynamics separately. An adaptive algorithm is developed to accomodate these uncertainties without knowing exactly the bounds of these uncertainties. The stability of the overall control system is proved by using Lyapunov function. The efiectiveness of the developed algorithms has been verifled on the platform FTLAB747.

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)0.001
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 score0.564
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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