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Record W1781591905 · doi:10.1109/acc.1995.529405

Robust and global stabilization of nonlinear systems

2005· article· en· W1781591905 on OpenAlexaff
Feng Liang, H.A. ElMaraghy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRobustness (evolution)Control theory (sociology)Nonlinear systemBounded functionVariable (mathematics)Robust controlControl variableMatching (statistics)Computer scienceStability (learning theory)Control systemMathematicsMathematical optimizationControl (management)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper investigates the robust and global stabilization problem of general nonlinear systems by introducing a variable index control approach. Variable index control laws can be derived based on a set of feasible multiple error indices, which always exist for general nonlinear systems, and the worst-case control strategy. The global stability and the robustness of the variable index control systems with bounded uncertainty are proved in the paper. The new approach can be applied to nonlinear systems which are not feedback-linearizable, and whose uncertainties are not required to satisfy any matching condition. The control actions are chatter-free. The feasibility of the variable index control approach has been demonstrated by design examples and numerical simulations.

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.

How this classification was reachedexpand

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 score0.487
Threshold uncertainty score0.293

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 head0.018
GPT teacher head0.214
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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