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Record W2137286278 · doi:10.1109/icsmc.2009.5346662

Robust control for robot manipulators by using only joint position measurements

2009· article· en· W2137286278 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
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)TrajectoryObserver (physics)Computer scienceTracking (education)Exponential stabilityStability (learning theory)Position (finance)Sliding mode controlRobot manipulatorRobust controlProperty (philosophy)RobotControl engineeringState observerStability theoryProcess (computing)Control systemControl (management)EngineeringArtificial intelligenceNonlinear system

Abstract

fetched live from OpenAlex

In this work, we propose an output feedback sliding mode control (SMC) method for trajectory tracking of robotic manipulators. The design process has two steps. First, we design a stable SMC approach by assuming that all state variables are available for feedback. Then, an output feedback version of this SMC design is presented which incorporates a model-free linear observer to estimate unknown velocity signals. We then show that the tracking performance under output feedback design can asymptotically recover the performance achieved under state feedback based SMC design. A detailed stability analysis is given which shows semi-global uniform ultimately boundedness property of all the closed loop signals. The proposed method is implemented and evaluated on a 2-DOF robotic system to illustrate the effectiveness of the theoretical development.

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 score0.968
Threshold uncertainty score0.736

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 head0.086
GPT teacher head0.247
Teacher spread0.162 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

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