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Record W2527461557 · doi:10.1109/aim.2016.7576758

Global stabilization of autonomous underactuated underwater vehicles in 3D space

2016· article· en· W2527461557 on OpenAlexaff
Morteza Mirzaei, Farzaneh Abdollahi, Nader Meskin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsConcordia University
Fundersnot available
KeywordsUnderactuationControl theory (sociology)CascadeActuatorKinematicsDegrees of freedom (physics and chemistry)Exponential stabilityVehicle dynamicsStability (learning theory)Computer scienceNonlinear systemTransformation (genetics)UnderwaterControl engineeringEngineeringControl (management)Artificial intelligencePhysicsAerospace engineering

Abstract

fetched live from OpenAlex

In this paper, global asymptotic stabilization of an autonomous underactuated underwater vehicle (AUUV) is investigated, where the number of actuators of the AUUV is less than the vehicle's degrees of freedom. The model that is considered describes both the kinematics and dynamics of the AUUV with six degrees of freedom and four actuators. To cope with the underactuation characteristics of AUUV a state transformation is proposed to change the model of the vehicle to a cascade nonlinear system. Then a switching control algorithm is proposed where the stability of the whole vehicle is guaranteed based on the stability properties of cascade systems. To illustrate the performance of the proposed approach, simulation results are provided.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.199
Teacher spread0.194 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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