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Record W2120406628 · doi:10.1109/acc.2006.1657204

Adaptive backstepping control of hydraulic manipulators with friction compensation using LuGre model

2006· article· en· W2120406628 on OpenAlexaff
Hongwei Zeng, Nariman Sepehri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBacksteppingControl theory (sociology)Controller (irrigation)Dynamical frictionLyapunov functionAdaptive controlCompensation (psychology)Nonlinear systemControl engineeringParametric statisticsAccelerationObserver (physics)Hydraulic cylinderExponential stabilityLyapunov stabilityComputer scienceEngineeringControl (management)MathematicsPhysics

Abstract

fetched live from OpenAlex

This paper addresses the backstepping control of hydraulic manipulators with friction compensation. A third-order nonlinear dynamic model is used for the controller design while LuGre dynamic friction model with non-uniform friction force variations characterizes the friction forces. The controller is augmented with adaptation laws to compensate for parametric uncertainties in the system dynamics. Acceleration feedback is avoided by using an adaptive observer. Asymptotic stability of the whole control system is proven via Lyapunov analysis. Simulation and experimental results are presented verifying the effectiveness of the developed controller

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 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 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 score0.664
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.018
GPT teacher head0.194
Teacher spread0.176 · 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 teacher head, 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

Citations14
Published2006
Admission routes1
Has abstractyes

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