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Record W1995785459 · doi:10.1109/acc.2014.6858961

Comparison of linear-quadratic and controllability criteria for actuator placement on a beam

2014· article· en· W1995785459 on OpenAlexaff
Steven Yang, Kirsten Morris

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStability and Controllability of Differential Equations
Canadian institutionsUniversity of WaterlooQueen's University
Fundersnot available
KeywordsActuatorControllabilityControl theory (sociology)PlantController (irrigation)Computer scienceQuadratic equationOptimal controlMathematicsMathematical optimizationControl (management)

Abstract

fetched live from OpenAlex

For control of a distributed parameter system, the performance of the controlled system is known to be dependent on the placement of the control actuator, and thus actuator location can be viewed as an additional variable in the controller design. The most common criterion in the engineering literature is to maximize a measure of the controllability. However, as shown here, this approach yields predictions that depend on the order of the model used for the calculations. Furthermore, minimizing the linear-quadratic cost is a common objective in controller design. It is reasonable then to choose the actuator location, as well as the controller itself, to minimize the linear-quadratic cost. In this paper, the performance of a controlled beam with the actuator chosen using these different criteria is examined. The effect of different weights in the cost function on the optimal actuator location is also examined. The control signal is calculated for a number of a different cases. It appears that optimal location of the actuator can improve performance without a corresponding increase in control effort, although possible saturation of control signals may be a concern in some applications.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.469

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 head0.031
GPT teacher head0.319
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

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

Citations7
Published2014
Admission routes1
Has abstractyes

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