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Variable-Gains Bi-Power Reaching Law of SMC with Terminal Model-Based Switching Surfaces for a 7-DoF Exoskeleton Robot

2024· article· en· W4406208895 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
TopicModular Robots and Swarm Intelligence
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsRobotTerminal (telecommunication)ExoskeletonControl theory (sociology)Variable (mathematics)Power (physics)Computer scienceEngineeringSimulationArtificial intelligencePhysicsMathematicsControl (management)Computer network

Abstract

fetched live from OpenAlex

This paper deals with the problem of robust trajectory tracking of a robot interacting with a human and subject to uncertainties and the problem of chattering in sliding mode. Indeed, a new controller for robotic manipulator systems using terminal model-based sliding manifolds is proposed. Moreover, a bi-power reaching law with variable-gains is designed to reduce the phenomenon of chattering and to ensure fixed-time stability of the exoskeleton robot trajectories into the sliding manifolds. The chattering is not reduced thanks to the new reaching law only but also thanks to the designed model-based sliding manifolds that allow a decoupled control inputs. The proposed controller is experimentally implemented on an upper-limb rehabilitation exoskeleton robot with seven rotary joints. A Comparison study with super-twisting second-order sliding mode is also presented to show the effectiveness of the developed technique.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.711

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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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