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Record W2912391416 · doi:10.1109/tmech.2019.2895222

Attitude Synchronization For Multiple 3-DOF Helicopters With Actuator Faults

2019· article· en· W2912391416 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/ASME Transactions on Mechatronics · 2019
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsUniversity of Toronto
FundersFundamental Research Funds for the Central UniversitiesGraduate Research and Innovation Projects of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsActuatorControl theory (sociology)Synchronization (alternating current)Attitude controlComputer scienceFault toleranceFault (geology)Control (management)Control engineeringTrack (disk drive)EngineeringArtificial intelligenceDistributed computingChannel (broadcasting)

Abstract

fetched live from OpenAlex

The attitude synchronization for multiple three-degree-of-freedom helicopters in the presence of system uncertainties and time-varying actuator faults is investigated. A fault-tolerant cooperative control algorithm based on robust adaptive control is proposed to synchronize attitudes of multiple helicopter systems in the case where some of the helicopters are subjected to both partial losses of control effectiveness and additive actuator faults. The proposed design is a distributed control method that allows each vehicle to track external reference signals merely in light of its neighborhood information. With the proposed design, time-varying actuator faults are tolerated without sacrificing the attitude synchronization performance. The effectiveness of the proposed control method is verified via a comparative experimental study.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.215
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