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Record W2059647479 · doi:10.5589/q12-004

Trajectory tracking control of flexible-joint space manipulators

2012· article· en· W2059647479 on OpenAlexaffvenue
Steve Ulrich, Jurek Z. Sąsiadek

Bibliographic record

VenueCanadian aeronautics and space journal · 2012
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)Jacobian matrix and determinantNonlinear systemSingular perturbationJoint stiffnessTrajectoryStiffnessControl engineeringRobotAdaptive controlEngineeringComputer scienceMathematicsControl (management)Artificial intelligenceStructural engineering

Abstract

fetched live from OpenAlex

Operational problems with robots in space relate to several factors. One of the most important factors is the elastic vibrations in the joints. In this paper, control strategies for endpoint tracking of a 12.6 m×12.6 m trajectory by a two-link space robotic manipulator are reviewed. Initially, a manipulator with rigid joints is actuated using a transpose jacobian control law and a model reference adaptive control system that adapts, in real-time, the control gains in response to errors between the actual system outputs and the ideal system outputs defined by a reference model. The rigid-joint dynamics model was pursued further to study a manipulator with flexible joints modeled with linear- and nonlinear-joint stiffness models. Then, the two rigid-joint control schemes were modified using the singular perturbation-based theory and applied for the control of both linear and nonlinear flexible-joint robot models. Finally, the rigid and flexible control systems described in this paper were evaluated in numerical simulations. Simulation results suggested that greatly improved tracking accuracy can be achieved by applying the adaptive control strategies.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.594

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 head0.191
Teacher spread0.177 · 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 designTheoretical or conceptual
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

Citations10
Published2012
Admission routes2
Has abstractyes

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