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Record W7132972912

Time optimal control of fluid catalytic cracking unit

2008· dissertation· W7132972912 on OpenAlexfundno aff
Bo Liao

Bibliographic record

VenueTSpace · 2008
Typedissertation
Language
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsOptimal controlFluid catalytic crackingConvergence (economics)Optimization problemSteady state (chemistry)ComputationNonlinear systemKinetic energyControl theory (sociology)
DOInot available

Abstract

fetched live from OpenAlex

Due to the high nonlinearity and complex reactions occurring in fluid catalytic cracking unit (FCCU), solving the time optimal control problem is especially challenging. Also constraints on the state variables make the problem even more difficult. However, the large throughput of FCCU, the change in operating conditions and the substantial economic benefits are the motivation behind this research. To solve the time optimal control problem based on the realistic model, the four-lump FCC model proposed by Ali and Rohani (1997) is used with small modifications. The modifications are justified by providing better agreement with the industrial data of the steady state and dynamic simulations. During the operation of a FCCU, the kinetic parameters may change and for adequate control, those parameters should be up-dated, especially when the feed is changed. In this work, Luus-Jaakola (LJ) optimization procedure is first applied to the estimation of kinetic parameters in the four-lump kinetic model for the riser reactor, and is then applied to the entire model of FCC unit. The results show better agreement with experimental data of Wang (Lee et al., 1989a) and the industrial data (Ali and Rohani, 1997). In addition, the significance of incorporating line search into LJ optimization procedure is illustrated by faster convergence and more accurate results for all the optimization problems in parameter estimation. The computations are reasonably fast, so in the future with faster computers the parameters can be up-dated on-line. Based on the developed dynamic model with the estimated kinetic parameters, a steady state optimization problem is solved to provide the desired optimal operation point for time optimal control. Compared with the industrial operating conditions, the optimal steady state obtained by using LJ optimization procedure increases the economic benefit by 17.33%. In solving the time optimal control problem of FCC unit, iterative dynamic programming (IDP) provides an efficient way to obtain the optimal control policy and to handle the constraints in a highly nonlinear dynamic system. The time to reach the vicinity of the desired state is significantly reduced with the use of time optimal control policy.

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 categoriesMeta-epidemiology (narrow)
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 score0.733
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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.

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
Published2008
Admission routes1
Has abstractyes

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