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Record W2158604423 · doi:10.1109/cdc.1997.657641

Robust regulation of a flexi-link manipulator based on a new modeling approach

2002· article· en· W2158604423 on OpenAlexaff
Mohammad Javad Yazdanpanah, Rajni V. Patel, K. Khorasani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)Position (finance)Link (geometry)Computer scienceBounded functionDeflection (physics)Norm (philosophy)Flexibility (engineering)Robust controlRobot manipulatorSystem dynamicsManipulator (device)RobotControl engineeringMathematicsControl systemControl (management)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

A new methodology for modeling a flexible-link manipulator with an arbitrarily large (infinite) number of deflection modes is presented where dynamics representing flexibility is treated as uncertainty. The synthesis is performed based on only the certain dynamics of the manipulator. In other words, the proposed approach to modeling actually characterizes, in some sense, a reduced-order model of the system. It is shown that the uncertainty treated in this way is norm-bounded. Control of the tip position is pursued by utilizing the multi-objective H/sub /spl infin// technique on the certain part of the dynamics. Robust regulation is obtained by minimizing the influence of the uncertainty on the tip position. The proposed strategy is applied to a single-link flexible arm and the simulation results verify the effectiveness of the analysis and design. Specifically, it is shown that by using the proposed scheme regulation of the tip position as achieved in a stable manner however by using the standard approach instability of the tip position occurs.

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 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 score0.984
Threshold uncertainty score0.350

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 head0.044
GPT teacher head0.187
Teacher spread0.143 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations8
Published2002
Admission routes1
Has abstractyes

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