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Record W2041764397 · doi:10.1016/j.cja.2014.12.006

Design of passive fault-tolerant flight controller against actuator failures

2014· article· en· W2041764397 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

VenueChinese Journal of Aeronautics · 2014
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsActuatorControl theory (sociology)Fault (geology)AirplaneController (irrigation)Lyapunov functionFault tolerancePolytopeEngineeringControl engineeringAmplitudeComputer scienceControl (management)Reliability engineeringNonlinear systemMathematicsAerospace engineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

The problem of designing passive fault-tolerant flight controller is addressed when the normal and faulty cases are prescribed. First of all, the considered fault and fault-free cases are formed by polytopes. As considering that the safety of a post-fault system is directly related to the maximum values of physical variables in the system, peak-to-peak gain is selected to represent the relationships among the amplitudes of actuator outputs, system outputs, and reference commands. Based on the parameter dependent Lyapunov and slack methods, the passive fault-tolerant flight controllers in the absence/presence of system uncertainty for actuator failure cases are designed, respectively. Case studies of an airplane under actuator failures are carried out to validate the effectiveness of the proposed approach.

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: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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