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DYNAMIC SLIDING MANIFOLDS FOR REALIZATION OF HIGH INDEX DIFFERENTIAL‐ALGEBRAIC SYSTEMS

2003· article· en· W2119466796 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

VenueAsian Journal of Control · 2003
Typearticle
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsConcordia UniversityHEC Montréal
Fundersnot available
KeywordsControl theory (sociology)ControllabilityRealization (probability)Nonlinear systemRobustness (evolution)MathematicsObservabilityState spaceDifferential algebraic equationManifold (fluid mechanics)Computer scienceApplied mathematicsDifferential equationOrdinary differential equationMathematical analysisEngineeringControl (management)

Abstract

fetched live from OpenAlex

ABSTRACT Differential‐algebraic equation (DAE) systems present a number of difficult problems in nonlinear simulation and control. One of the key difficulties is that DAEs are not expressed in an explicit state space form required by many simulation and control design methods. In this paper, the problem is addressed using a new approach that constructs an explicit state space approximation of the DAEs using a sliding controller. The state space model can in turn be used with existing nonlinear control and simulation methods. This procedure, known as realization, is achieved by developing a boundary layer sliding controller with a dynamic sliding manifold. The approach builds on previous realization methods proposed by the author that employ a static sliding control surface. The approach is generalized by employing a dynamic sliding manifold which allows much greater freedom in determining optimality, robustness, and convergence of the realization than previous methods allow. The necessary criteria for key properties such as convergence, stability, and controllability of this new method are proven using a special type of sliding normal form. Furthermore, the important property of observability for sliding realizations is established for the first time by analyzing the convergence of local eigenvectors of the approximation. Together these results establish a new general framework for realization of a large class of nonlinear high index DAE systems.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.024
GPT teacher head0.312
Teacher spread0.288 · 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