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Record W2997543521 · doi:10.1109/tmech.2019.2962663

Improving Tracking Performance of Nonlinear Uncertain Bilateral Teleoperation Systems With Time-Varying Delays and Disturbances

2019· article· en· W2997543521 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2019
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsControl theory (sociology)TeleoperationComputer scienceNonlinear systemParametric statisticsControl engineeringStability (learning theory)Transmission (telecommunications)Haptic technologyTracking (education)Control (management)EngineeringSimulationMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

In this article, an adaptive nonsingular terminal sliding-mode (ANTSM) method is proposed for the motion tracking control of a bilateral teleoperation system. Efforts in this article seek to improve the position tracking performance of nonlinear systems subject to time-varying network delays, parametric uncertainties, and unknown external disturbances and frictions. Another issue addressed in this article is the common delay-induced phase shift of tracking profiles in many control methods, which is greatly reduced by introducing a novel mixed type of feedback signals in the ANTSM control design. Furthermore, the proposed adaptive control design with two online-estimated compensatory bounds removes the requirement of exact knowledge of network delays and disturbance bounds as a prior. In the master side, a force predictor is used to estimate the current environmental force for the reference signal generator. Therefore, the direct transmission of force signals is avoided. By comparing with the existing model-based and model-free methods, numerical simulation results with six-degree-of-freedom manipulators illustrate the merits of the developed robust and adaptive controllers. Experimental results with two Phantom Omni devices are also provided to demonstrate the effectiveness and the significant performance improvements of the proposed controllers.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.744

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 head0.007
GPT teacher head0.187
Teacher spread0.181 · 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