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Record W2130346454 · doi:10.1243/09596518jsce529

Hybrid sliding sector control for a wheeled mobile robot

2008· article· en· W2130346454 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 · 2008
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsControl theory (sociology)Mobile robotLyapunov functionHybrid systemHolonomicControl (management)Control systemSliding mode controlControl engineeringComputer scienceRobotEngineeringNonlinear systemArtificial intelligence

Abstract

fetched live from OpenAlex

This paper proposes a hybrid control algorithm with sliding sectors for the control of a wheeled mobile robot (WMR), which is a non-holonomic system. The WMR control system with a set of available or pre-designed control laws is considered as a hybrid system with a set of subsystems. The WMR with one of control laws forms a non-linear subsystem of the hybrid system. The subsystems may be unstable but for each subsystem of the hybrid system, a stable subset called a sliding sector is designed such that a Lyapunov function candidate decreases inside the sliding sector. The hybrid control rule is used to stabilize the WMR control system by switching the hybrid system among its subsystems such that the system is always inside a sliding sector of some subsystem. The proposed hybrid sliding sector control algorithm has been successfully implemented to the real-time control of WMR with good control performance.

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: none
Teacher disagreement score0.596
Threshold uncertainty score0.868

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 head0.008
GPT teacher head0.176
Teacher spread0.169 · 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