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Record W2154327602 · doi:10.1109/cdc.2010.5717315

Performance limitations of the servomechanism problem when the number of tracking/disturbance poles increases

2010· article· en· W2154327602 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIterative Learning Control Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsServomechanismControl theory (sociology)Disturbance (geology)Tracking (education)Measure (data warehouse)Controller (irrigation)sortMathematicsRobust controlComputer scienceIndex (typography)Control systemEngineeringControl (management)Control engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, we study the cheap control problem and determine what some of the inherent system limitations are in achieving high performance for LTI systems. In particular, we observe that a fundamental difficulty in designing a high performance controller for a system may occur, which is related to the infinite transmission zero structure of the system. A continuous measure, called the Toughness Index, is introduced to characterize such limitations. We then apply these results to the robust servomechanism problem (RSP), and show that the Toughness Index of the RSP becomes worst as the number of tracking/disturbance poles to be tracked/regulated increases. This implies that high performance control in the RSP cannot be obtained for a large number of tracking/disturbance poles, even for minimum phase systems.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.207

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 head0.014
GPT teacher head0.203
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

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Citations0
Published2010
Admission routes1
Has abstractyes

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