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Discrete Output Regulator Design for a Coupled ODE-PDE System

2020· article· en· W3045619108 on OpenAlexaff
Guilherme Ozorio Cassol, Stevan Dubljević

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOdeControl theory (sociology)BacksteppingRegulatorDiscretizationController (irrigation)TrajectoryMathematicsExponential stabilityComputer scienceApplied mathematicsAdaptive controlNonlinear systemControl (management)Mathematical analysis

Abstract

fetched live from OpenAlex

This manuscript addresses the design of a discrete regulator for an unstable coupled ODE-PDE cascade system with a recycle stream. The proposed regulator design considers a state feedback gain control law with the input applied to the ODE system. The controller has to ensure the closed-loop system stability and proper output tracking of reference signals. The discrete nature of the design is achieved by application of structure preserving Cayley-Tustin discretization to the coupled system given by a first-order ODE and a first-order hyperbolic PDE without the use of any spatial approximation and/or model order reduction. For the stabilization, the backstepping methodology is applied to ensure the system is mapped to the desired stable target system. To achieve adequate tracking, an exosystem representation is assumed in the design and leads to the corresponding Sylvester equation. The corresponding relationship between the continuous and discrete setting is shown. Finally, the simulations show the performance of the designed regulator for proper stabilization and trajectory tracking.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.681
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.219
GPT teacher head0.369
Teacher spread0.150 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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