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Record W2107168223 · doi:10.1177/2041304110394566

Chattering reduction on the dynamic tracking control of a nonholonomic mobile robot using exponential sliding mode

2011· article· en· W2107168223 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

VenueProceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsControl theory (sociology)TrajectoryMobile robotSliding mode controlNonholonomic systemReduction (mathematics)Controller (irrigation)Tracking (education)Computer scienceExponential functionMode (computer interface)Tracking errorRobotControl engineeringEngineeringArtificial intelligenceMathematicsControl (management)Nonlinear systemPhysics

Abstract

fetched live from OpenAlex

This paper considers the problem of improving chattering reduction and trajectory tracking along a desired trajectory for a mobile robot. It is proposed that exponential sliding mode control is an effective solution to reduce chattering for the trajectory tracking of a nonholonomic mobile robot. Compared to conventional and second-order sliding modes, the developed sliding mode control reduces chattering and delivers a high dynamic tracking performance in a steady state mode. The developed algorithm instructs the robot to keep moving continuously on the desired trajectory while reducing tracking errors. Experimental results on a wheeled mobile robot are presented to demonstrate the performance of the exponential sliding mode controller algorithm compared to both conventional and second-order sliding mode algorithms.

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: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.196
Teacher spread0.182 · 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