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Record W2122670248 · doi:10.1109/tcst.2005.860517

Heuristic design of a fuzzy controller for a flexible robot

2006· article· en· W2122670248 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

VenueIEEE Transactions on Control Systems Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsFuzzy logicControl theory (sociology)HeuristicTrajectoryFuzzy control systemController (irrigation)ScalingComputer scienceMembership functionDefuzzificationFuzzy setRobotMathematicsFuzzy numberMathematical optimizationControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

A ratio is identified as a heuristic to assist in designing fuzzy logic system (FLS) controllers with a low number of membership functions (MFs), high tracking precision, and fast execution time for the control of a two-link flexible space robot. Comparing simulation results for an FLS with three, five, seven, and nine triangular and Gaussian membership functions provides a combination of type and number of MF for optimal tracking control and execution time. Optimal control occurs when the ratio of the FLS output scaling gain to the number of MFs is equal to the output variable universe of discourse. The optimal FLS design is chosen with three triangular membership functions at an output scaling gain of 15, giving a design ratio of five and execution time of 1 min 40 s while tracking a square trajectory

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 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 score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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 head0.009
GPT teacher head0.200
Teacher spread0.192 · 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