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Record W2330755182 · doi:10.1115/fpmc2013-4447

Position Tracking of a Pneumatic Actuator Using Backstepping-Sliding Mode Control With Adaptive Friction Observer

2013· article· en· W2330755182 on OpenAlexafffund
Ramhuzaini Abd Rahman, Nariman Sepehri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Manitoba
FundersMinistry of Higher Education, MalaysiaNatural Sciences and Engineering Research Council of CanadaUniversiti Tun Hussein Onn Malaysia
KeywordsControl theory (sociology)BacksteppingObserver (physics)ActuatorPneumatic actuatorState observerController (irrigation)Sliding mode controlPneumatic cylinderServomechanismTracking (education)Position (finance)Control engineeringComputer scienceAdaptive controlEngineeringCylinderNonlinear systemArtificial intelligenceControl (management)PhysicsMechanical engineering

Abstract

fetched live from OpenAlex

In this paper, an enhanced sliding mode control (SMC)-based controller known as backstepping-sliding mode control (B-SMC) with an adaptive friction observer is proposed for position tracking control of pneumatic actuators. The adverse effect of friction encountered in the pneumatic actuators which play a major role in pneumatic servo system is highlighted and a solution to rectify this is proposed using an adaptive LuGre-based friction observer for friction compensation. The B-SMC is experimentally applied, for the first time, on a double-acting single-rod industrial pneumatic cylinder. Comprehensive derivation as well as stability proof of the controller is presented. The performance of B-SMC with and without the friction observer is experimentally investigated. From the results, it is clearly observed that the B-SMC with the adaptive friction observer performs better (i.e. reduces the tracking as well steady-state errors of up to 30%) than the one without friction observer. Thus, the adaptive friction observer of B-SMC is identified as the key element that improved the control performance by compensating the adverse effect of friction during the position tracking tasks.

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: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.547

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 head0.020
GPT teacher head0.210
Teacher spread0.190 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

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