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Record W2092732409 · doi:10.1155/2008/489124

Discrete‐Time Sliding‐Mode Control of Uncertain Systems with Time‐Varying Delays via Descriptor Approach

2008· article· en· W2092732409 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

VenueJournal of Control Science and Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsUniversity of Saskatchewan
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)Bounding overwatchDiscrete time and continuous timeSliding mode controlController (irrigation)Mode (computer interface)Linear matrix inequalityMathematicsSurface (topology)Transformation (genetics)Observer (physics)Transformation matrixMatrix (chemical analysis)Class (philosophy)Model transformationComputer scienceControl (management)Mathematical optimizationNonlinear systemPhysicsGeometry

Abstract

fetched live from OpenAlex

This paper considers the problem of robust discrete‐time sliding‐mode control (DT‐SMC) design for a class of uncertain linear systems with time‐varying delays. By applying a descriptor model transformation and Moon′s inequality for bounding cross terms, a delay‐dependent sufficient condition for the existence of stable sliding surface is given in terms of linear matrix inequalities (LMIs). Based on this existence condition, the synthesized sliding mode controller can guarantee the sliding‐mode reaching condition of the specified discrete‐time sliding surface for all admissible uncertainties and time‐varying delays. An illustrative example verifies the effectiveness of the proposed method.

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 score0.627
Threshold uncertainty score0.861

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 communication0.0000.001
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 head0.181
Teacher spread0.174 · 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