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Record W4401917067 · doi:10.1080/00207721.2024.2394568

Velocity observer design for a class of uncertain nonlinear mechanical systems: a self-adaptive fuzzy logic-based approach

2024· article· en· W4401917067 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

VenueInternational Journal of Systems Science · 2024
Typearticle
Languageen
FieldComputer Science
TopicFuzzy Logic and Control Systems
Canadian institutionsUniversity of Waterloo
FundersTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsNonlinear systemControl theory (sociology)Fuzzy logicClass (philosophy)Observer (physics)MathematicsMechanical systemComputer scienceControl engineeringEngineeringArtificial intelligencePhysicsControl (management)

Abstract

fetched live from OpenAlex

This study focused on designing a smooth velocity observer (VO) for mechanical systems whose mathematical model is uncertain. The uncertainties that appear in the observer dynamics are, via utilising their universal approximation property, modelled with fuzzy logics. A novel self-adaptive fuzzy logic (SAFL)-based term in which control representative value matrix (CRVM), centres and widths of membership function are all dynamically updated is used as part of the observer design. Through the application of Lyapunov-type stability analysis techniques, the practical stability of the observed velocity error was guaranteed. The outcomes derived from experimentation on a planar robotic manipulator are showcased to illustrate the performance of the devised VO design.

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)0.006
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: Methods · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.000
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 head0.062
GPT teacher head0.289
Teacher spread0.227 · 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