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Record W2117925921 · doi:10.1109/tfuzz.2005.859322

Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping and application to chemical processes

2005· article· en· W2117925921 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 Fuzzy Systems · 2005
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsLakehead University
Fundersnot available
KeywordsControl theory (sociology)Decoupling (probability)BacksteppingNonlinear systemMIMOFuzzy control systemFuzzy logicMathematicsBounded functionInternal modelComputer scienceAdaptive controlControl engineeringControl (management)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Fuzzy approximate disturbance decoupling concept is introduced for a class of multiple-input-multiple-output (MIMO) nonlinear systems with completely unknown nonlinearities. Based on backstepping technique, a fuzzy almost disturbance decoupling control scheme is proposed. The fuzzy controllers guarantee internal uniform ultimate boundedness of the closed-loop adaptive systems and render a bounded approximate L/sub 2/ gain from the disturbance input to the output. The developed design scheme is applied to control a two continuous stirred tank reactor process. The simulation results illustrate the effectiveness of the method proposed in this paper.

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 score0.919
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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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