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Record W1965109547 · doi:10.1115/esda2006-95033

Design of a Fuzzy Controller for an Underwater Vehicle Aiming at a Stationary Target

2006· article· en· W1965109547 on OpenAlexaff
Farhood Azarsina, Hassan Sayyaadi

Bibliographic record

VenueVolume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsNational Research Council Canada
FundersSharif University of Technology
KeywordsSubmarineController (irrigation)Control theory (sociology)Fuzzy logicComputer scienceUnderwaterPosition (finance)Point (geometry)Motion controlControl engineeringFuzzy control systemRobotArtificial intelligenceEngineeringControl (management)MathematicsMarine engineering

Abstract

fetched live from OpenAlex

In this paper, on the basis of a robust algorithm for the analysis of the 6 DOF motion of an underwater vehicle in calm water, after presenting the dynamics model and simulating motion, the model is put in the closed loop control to perform a controlled mission. The mission is defined as to navigate the submarine toward a desired point in the vertical plane. In performing the mission, the least time and of course the least position error with respect to the target point is aimed. The designed controller based on fuzzy logic and thus adapted to the human patterns for navigation, with a simple structure, performs the mission accurately. The intelligent structure of the fuzzy controller, results in a spectacular capability in target finding; such that by the increase of mission duration, the submarine, which never completely stops in this modeling, reaches the target point multiple times. Several simulations of the controlled motion, changing the coordinates of target point, proved the controller effectiveness.

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 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)
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 score0.908
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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 head0.008
GPT teacher head0.190
Teacher spread0.181 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueVolume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems EngineeringSame topicUnderwater Vehicles and Communication SystemsFrench-language works237,207