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Record W2999942356 · doi:10.12700/aph.16.10.2019.10.10

Design of a Composite State Convergence Controller for a Nonlinear Telerobotic System

2019· article· en· W2999942356 on OpenAlex
Muhammad Usman Asad, Umar Farooq, Jason Gu, Valentina Emilia Bălaş, Ghulam Abbas, Marius M. Bǎlaş

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueActa Polytechnica Hungarica · 2019
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvergence (economics)Nonlinear systemControl theory (sociology)Controller (irrigation)Control engineeringComposite numberComputer scienceState (computer science)EngineeringArtificial intelligenceControl (management)AlgorithmPhysics

Abstract

fetched live from OpenAlex

This paper presents the design of a reduced complexity state convergence controller, termed as composite state convergence controller, for a single degree-offreedom nonlinear telerobotic system. First, nonlinear master and slave models are feedback-linearized and composite states are formed by combining their respective position and velocity signals. These composite master and slave states along with the operator's force are then transmitted across the communication channel instead of full states. In this way, the complexity of communication structure is reduced. An augmented system composed of composite master and slave states is finally constructed and method of state convergence is applied to compute the control gains of the proposed scheme. It is shown that position and velocity states of the master and slave systems still converge in the absence and presence of time delays, even though the design is based on the reduced order composite system. The validity of the proposed scheme is confirmed through MATLAB simulations as well as semi-real time experiments.

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 score0.932
Threshold uncertainty score0.714

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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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