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Record W2464082415 · doi:10.1002/cjce.22551

PI controller design for a TITO system based on delay compensated structure and direct synthesis

2016· article· en· W2464082415 on OpenAlexvenueno aff
Qibing Jin, Lingjia Zhu, Qi Wang, Beiyan Jiang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Design
Canadian institutionsnot available
FundersMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsControl theory (sociology)Transfer functionPID controllerCompensation (psychology)Controller (irrigation)Process (computing)Computer scienceFunction (biology)MathematicsControl engineeringEngineeringControl (management)Temperature control

Abstract

fetched live from OpenAlex

Abstract The present study suggests a new scheme to design a decentralized PI controller for two‐input two‐output (TITO) processes. The decentralized controller is obtained from the direct synthesis method. The decoupler is derived from a modified decoupler and minimizes the interaction between the loops. Then a new reduced method based on equivalent transfer function (ETF) with relative gain array concept and relative normalized relative gain array concept reduces the decoupled process transfer functions to first‐order plus time delay (FOPTD) forms. Further, two PI controllers are obtained in the proposed delay‐compensated configuration in terms of the only parameter in every individual loop for the FOPTD transfer functions. Three illustrative examples demonstrate that the performance is verified on the original interactive system and show the effectiveness of the proposed design method. The results confirm the superior performance of the proposed compensation configuration in nominal and robust cases. The proposed method also offers several important advantages compared to other previous 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.165
Teacher spread0.157 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Quick stats

Citations4
Published2016
Admission routes1
Has abstractyes

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