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Record W2775736372 · doi:10.1109/m2vip.2017.8211436

Adaptive fuzzy dynamic surface controller for positioning of vessels

2017· article· en· W2775736372 on OpenAlex
Yuanhui Wang, Yulong Tuo, Mingyu Fu, Simon X. Yang

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Guelph
FundersFundamental Research Funds for the Central UniversitiesCentral University Basic Research Fund of ChinaChina Scholarship Council
KeywordsDynamic positioningControl theory (sociology)Controller (irrigation)Fuzzy logicHeading (navigation)Computer scienceFuzzy control systemControl engineeringAdaptive controlOpen-loop controllerEngineeringClosed loopControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a new adaptive fuzzy controller is proposed for the dynamic positioning system of vessels with unknown time-varying dynamic model parameters and environmental disturbances. This controller comprises of an adaptive fuzzy logic and the dynamic surface control (DSC) technique. The adaptive fuzzy system is used to estimate the uncertainties induced by unknown dynamic model parameters and disturbances. By using the DSC technique, the proposed controller can reduce the computational complexity. The proposed adaptive fuzzy positioning controller can keep the vessel at the desired positions and heading, while making all signals of the closed-loop positioning system within the uniform ultimate boundedness. The effectiveness of the proposed controller is demonstrated through simulations for a floating production storage and offloading vessel.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score0.485

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 communication0.0000.000
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 head0.018
GPT teacher head0.260
Teacher spread0.243 · 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

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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