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Record W4409764396 · doi:10.3390/act14050209

Speed Sensorless Motion Control Scheme for a Robotic Manipulator Under External Forces and Payload Changes

2025· article· en· W4409764396 on OpenAlex
Jorge Alfredo Montero Pacheco, David Cortés-Vega, Hussain Alazki

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueActuators · 2025
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsnot available
Fundersnot available
KeywordsPayload (computing)Control theory (sociology)Manipulator (device)Scheme (mathematics)Robot manipulatorControl engineeringMotion controlComputer scienceMotion (physics)Robotic armEngineeringRobotControl (management)Artificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper proposes the design of a speed sensorless robust discontinuous controller for the trajectory tracking problem of a 5-DOF robotic manipulator under payload changes and torque disturbances in the joints. The developed observer-based controller is capable of performing trajectory tracking, ensuring stability, fast error convergence and speed sensorless operation. In order to avoid joint speed measurement, an estimation scheme based on a differentiation algorithm is implemented to estimate it. Simulation tests developed in MATLAB/Simulink are presented to show the high performance of the proposed scheme for two different trajectories with the model of the CRS Catalyst-5 by Thermo Electron®, Burlington, ON, Canada.

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 score0.779
Threshold uncertainty score0.717

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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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