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Record W4412456679 · doi:10.1080/00207721.2025.2529490

A robust end effector tracking controller formulation for robot manipulators actuated via brushless DC motors with uncertainties

2025· article· en· W4412456679 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

VenueInternational Journal of Systems Science · 2025
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsControl theory (sociology)DC motorControl engineeringRobot manipulatorRobot end effectorController (irrigation)Tracking (education)RobotComputer scienceRobust controlEngineeringArtificial intelligenceControl (management)Control systemPsychology

Abstract

fetched live from OpenAlex

A robust controller formulation for the precise end effector tracking of robot manipulators having uncertainties throughout its entire mechanical and actuator subsystems is presented. The formulated robust controller achieves practical end effector tracking, even in the presence of uncertainties in the kinematic and dynamic parameters of the mechanical subsystem and the electrical parameters of the actuator subsystem. Specifically, a robust backstepping type controller formulation that makes use of the nominal values of the system parameters is designed to ensure an exponentially convergent, practical end effector tracking result. The stability and global convergence of the controller formulation are ensured via Lyapunov type arguments and extensive experimental studies conducted on custom–built planar robotic manipulator demonstrate the feasibility of the proposed method.

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: Empirical · Consensus signal: none
Teacher disagreement score0.717
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.023
GPT teacher head0.262
Teacher spread0.239 · 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