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Record W2037969209 · doi:10.1109/tcst.2014.2363169

Diagnosis of Oscillations Between Controller Tuning and Harmonic External Disturbances

2014· article· en· W2037969209 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsControl theory (sociology)Controller (irrigation)HarmonicComputer sciencePhysicsControl engineeringAcousticsControl (management)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper studies the properties of linear systems described by discrete-time stochastic dynamic models and the conditions that yield an oscillatory response. Feedback loops that are oscillatory due to the controller tuning fall into this category of systems. Therefore, analyzing linear systems with oscillatory responses reveals the properties of self-oscillatory feedback loops. It is shown that in the presence of random disturbances, the oscillation due to the controller has a varying amplitude and phase even though the oscillation frequency is constant. The autocorrelation function of these types of oscillatory signals has a decay ratio and does not have a deterministic amplitude of oscillation. These properties can be utilized in distinguishing between the controller induced and externally introduced oscillations. Two hypothesis tests are developed to facilitate a solution for the above stated oscillation diagnosis problem.

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.

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 score0.816
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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