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Record W2112712195 · doi:10.1109/tcst.2004.838570

Fault-tolerant control of a servohydraulic positioning system with crossport leakage

2004· article· en· W2112712195 on OpenAlexaff
Mark Karpenko, Nariman Sepehri

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsControl theory (sociology)Leakage (economics)ActuatorQuantitative feedback theoryEngineeringFault toleranceControl engineeringController (irrigation)Control systemComputer scienceRobust controlControl (management)Reliability engineering

Abstract

fetched live from OpenAlex

This brief details the design of a fault-tolerant control (FTC) scheme for a servohydraulic positioning system with a faulty actuator piston seal that introduces internal (crossport) leakage between the actuator chambers. It is shown that the leakage fault changes the plant type from 1 to 0, decreases the open-loop gain, and increases the effective damping. A fixed-gain linear time-invariant control law is synthesized via quantitative feedback theory (QFT) to guarantee satisfaction of a priori-defined reference tracking and stability requirements, despite the occurrence of the leakage fault. Experiments verify the ability of the designed fault-tolerant controller to compensate for the degrading effects of this fault. Experiments also demonstrate the superior tracking performance of the FTC scheme as compared to a control loop in which the effects of the leakage fault are not considered in the controller design.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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
GenreMethods

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

Citations56
Published2004
Admission routes1
Has abstractyes

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