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Record W2141171297 · doi:10.1049/iet-est.2013.0047

Fault tolerant control and tracking application of 7000 m manned submarine vehicle

2015· article· en· W2141171297 on OpenAlexaff
Bing Sun, Daqi Zhu, Zhen Hu, Simon X. Yang

Bibliographic record

VenueIET Electrical Systems in Transportation · 2015
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Guelph
FundersBeijing Municipal Science and Technology CommissionScience and Technology Commission of Shanghai MunicipalityMinistry of Science and Technology of the People's Republic of ChinaShanghai Municipal Education CommissionNational Natural Science Foundation of China
KeywordsSubmarineConvergence (economics)Particle swarm optimizationTracking (education)Fault toleranceFault (geology)Control theory (sociology)EngineeringControl engineeringControl (management)Computer scienceArtificial intelligenceReliability engineeringAlgorithmMarine engineering

Abstract

fetched live from OpenAlex

A thruster fault tolerant control method based on quantum‐behaved particle swarm optimisation (QPSO) is investigated for 7000 m JIAOLONG manned submarine vehicle (MSV) in this study. First, QPSO is selected for the fast convergence and global search capability. To show the efficiency of QPSO fault tolerant method, PSO is studied as a comparison research. Then, to further apply the proposed method, tracking control problem with thruster fault is taken into consideration. Finally, simulations illustrate the performance of the derived fault tolerant tracking control technique.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2015
Admission routes1
Has abstractyes

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