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Record W2025291222 · doi:10.1002/rnc.1411

Switching contact task control in hydraulic actuators: Stability analysis and experimental evaluation

2009· article· en· W2025291222 on OpenAlexaff
Pooya Sekhavat, Q. Wu, Nariman Sepehri

Bibliographic record

VenueInternational Journal of Robust and Nonlinear Control · 2009
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsControl theory (sociology)ActuatorSliding mode controlController (irrigation)Lyapunov functionPosition (finance)Lyapunov stabilityEquilibrium pointExponential stabilityTask (project management)Motion controlComputer scienceControl engineeringControl (management)EngineeringMathematicsPhysicsRobotArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract A switching contact task control for hydraulic actuators is proposed. The controller is built upon three individually designed control laws for three phases of motion: (1) position regulation in free space, (2) impact suppression and stable transition from free to constrained motion and (3) force regulation in sustained‐contact motion. The position and force control schemes are capable of asymptotic set‐point regulation in the presence of actuator friction and without the complexity of sliding mode or adaptive control techniques. The intermediate impact control scheme is included for the first time to dampen the undesirable impacts and dissipate the impact energy that could potentially drive the whole system unstable. The solution concept and the stability of the complete switching control system are analyzed rigorously using the Filippov's solution concept and the concept of Lyapunov exponents. Both computer simulations and experiments are carried out to demonstrate the efficacy of the designed switching control law. Copyright © 2009 John Wiley & Sons, Ltd.

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)0.001
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 score0.488
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.257
Teacher spread0.246 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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