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Sliding Mode Reconfigurable Fault Tolerant Control for Nonlinear Aircraft Systems

2014· article· en· W2089752787 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.

Bibliographic record

VenueJournal of Aerospace Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsActuatorControl theory (sociology)Nonlinear systemSliding mode controlController (irrigation)Flight control surfacesFault toleranceEngineeringFault detection and isolationFault (geology)Control engineeringControl systemMode (computer interface)Lyapunov stabilityComputer scienceControl (management)AerodynamicsAerospace engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a sliding mode reconfigurable control algorithm without dedicated fault detection and identification module is developed for nonlinear aircraft systems with partial loss fault or total failure such as stuck or floating. The redundant actuators are integrated with the regular actuators in the controller seamlessly when faults or failures occur in the regular actuators. This method monitors the sliding surface to decide if the redundant actuator should be activated. The stability of the control system was proved by using Lyapunov method, and the effectiveness of the control system is validated by the simulation results of longitudinal control of a nonlinear model of Boeing 747.

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 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 score0.906
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.203
Teacher spread0.198 · 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