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ROBUST CONTROL DESIGN FOR A PLANAR PARALLEL ROBOT

2007· article· en· W2041557901 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueInternational Journal of Robotics and Automation · 2007
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer sciencePlanarControl (management)Control theory (sociology)Artificial intelligenceOperating system

Abstract

fetched live from OpenAlex

In this paper a control design approach termed the Convex Integrated Design (CID) method is used to design a robust controller for a high-speed, high-accuracy planar parallel robot. A controller that simultaneously satisfies four closed-loop performance specifications---the first three define closed-loop performance (i.e. the high-speed and high-accuracy motion of the platform with a limited control effort) and the fourth is a robustness specification that guarantees the previous three closed-loop performance specifications are satisfied in the presence of dynamic model uncertainty (e.g., unknown payload) and external disturbances---is determined using the CID method. Experimental results are presented that verify both the performance of the resultant control design and the CID method, applied to this planar parallel manipulator.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.235
Threshold uncertainty score0.305

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 head0.022
GPT teacher head0.238
Teacher spread0.216 · 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