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Record W2162996718 · doi:10.1109/3477.826955

Experimental results on discrete-time nonlinear adaptive tracking control of a flexible-link manipulator

2000· article· en· W2162996718 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 Systems Man and Cybernetics Part B (Cybernetics) · 2000
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)Nonlinear systemController (irrigation)Feedback linearizationA priori and a posterioriAdaptive controlLinearizationPayload (computing)Computer scienceTracking (education)MathematicsControl (management)Network packet

Abstract

fetched live from OpenAlex

The aim of this paper is to develop and implement a nonlinear adaptive control scheme for a single-link flexible manipulator. The controller is designed based on a discrete-time nonlinear model of the arm. The model is derived by using the forward difference method (Euler approximation). The output redefinition concept is then used so that the associated zero dynamics corresponding to the new output is guaranteed to be exponentially stable. An indirect adaptive linearizing controller is developed for the resulting minimum phase system where the "payload mass" is assumed to be unknown but its upper bound is assumed to be known a priori. The performance of the adaptively controlled closed-loop system is investigated by both numerical simulations and experimental results. The proposed controller is also compared experimentally with those of nonadaptive feedback linearization and conventional proportional derivative (PD) control strategies.

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: Empirical
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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