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Record W2889054297 · doi:10.1109/icca.2018.8444195

Synchronized path following for LTI systems and closed paths: Laboratory implementation

2018· article· en· W2889054297 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
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSynchronizingControl theory (sociology)Path (computing)LTI system theoryLeverage (statistics)Computer scienceLinear systemMotion planningSynchronization (alternating current)Control (management)Topology (electrical circuits)MathematicsRobot

Abstract

fetched live from OpenAlex

This paper examines a synchronized path following control design problem for a collection of homogenous, minimum phase, linear time-invariant systems assigned closed curves in their output space. In the first part of the paper we define a path following normal form for LTI systems. We isolate the role that the zero dynamics play in determining the feasibility of using the path following normal form for control design. In the second part of the paper we leverage recent results from the literature on synchronizing LTI systems to develop synchronizing controllers. The main result is a distributed feedback law that drives all the agents to their respective paths and ensures path invariance while simultaneously synchronizing their positions along the path. Laboratory results are presented to illustrate the effectiveness of the proposed approach.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.243

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 head0.011
GPT teacher head0.284
Teacher spread0.273 · 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

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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