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Record W1991340728 · doi:10.1109/icma.2007.4303718

Sliding-Mode Observer Based Adaptive Control for Servo Actuator with Friction

2007· article· en· W1991340728 on OpenAlexafffund
Wenfang Xie, Zhongyu Zhao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIterative Learning Control Systems
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)ActuatorObserver (physics)State observerServomotorServomechanismCompensation (psychology)Controller (irrigation)Dynamical frictionSliding mode controlServoFriction torqueComputer scienceAdaptive controlTorqueMode (computer interface)Control engineeringEngineeringControl (management)Nonlinear systemArtificial intelligenceMaterials sciencePhysics

Abstract

fetched live from OpenAlex

In this paper, a novel sliding-mode observer based adaptive controller is developed for the servo actuators with friction. The LuGre dynamic friction model is adopted for adaptive friction compensation. A sliding-mode observer is proposed to estimate the internal friction state of LuGre model. Based on the estimated friction state, adaptation laws are designed to compensate the unknown friction and load torque. The stability of the adaptive controller with sliding-mode observer is analyzed. The position tracking performance has been verified through experimental results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2007
Admission routes2
Has abstractyes

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