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Record W3114927886 · doi:10.1002/rnc.5377

Energy‐based output regulation for stochastic port‐Hamiltonian systems

2020· article· en· W3114927886 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

VenueInternational Journal of Robust and Nonlinear Control · 2020
Typearticle
Languageen
FieldEngineering
TopicControl and Stability of Dynamical Systems
Canadian institutionsYork University
FundersNational Natural Science Foundation of China
KeywordsControl theory (sociology)Hamiltonian (control theory)Hamiltonian systemInverted pendulumTracking errorMathematicsComputer scienceMathematical optimizationNonlinear systemPhysicsControl (management)Mathematical analysis

Abstract

fetched live from OpenAlex

Abstract This article investigates the output regulation for stochastic port‐Hamiltonian systems (SPHSs) subject to sinusoidal disturbances. An energy‐based regulation scheme with an internal model unit is proposed by exploiting the stochastic Hamiltonian structure, which drives the tracking error to the origin while maintaining asymptotical stability in probability of the closed‐loop system. An energy‐based robust regulation scheme as well as an alternative condition is then developed without solving Hamilton–Jacobi–Issacs inequalities. The proposed regulators preserve the stochastic Hamiltonian structure of the disturbed SPHS by coordinate transformation. Hence the output regulation problems fall into the stabilization framework for SPHSs and there is no need to solve regulator equations. These results cover the stabilization of SPHSs and the output regulation of deterministic port‐Hamiltonian systems. Simulations on an inverted pendulum show the effectiveness of the proposed methods.

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)0.000
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: none
Teacher disagreement score0.979
Threshold uncertainty score0.406

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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