Plant‐wide control for processes with recycle and narrow feasible sets
Bibliographic record
Abstract
Abstract Recycling mass and energy is a feature in almost all plants and industries. It is reported as an inevitable characteristic in actual industries due to differences between the designed processes and implementation. When a process is set, engineers identify inefficiencies in the planned performance and utilize recycles to try to reduce this difference. However, although recycles help in improving a plant's overall performance compared with a serial arrangement, its effect on dynamic plant behaviour is seldom considered, and these changes begin to impact the features of processes like controllability and stability. Similarly, even though recycles affect the feasible region of individual equipment, its effect is not verified. Based on the aforementioned background, several studies have demonstrated that advanced control strategies allow for the improvement of the dynamic behaviour of complex plants. Different techniques, such as model‐based predictive control and plant‐wide control (PWC), also show that their implementation reduces the effects of recycles. However, there is no explicit methodology to design these controllers and address the impacts of recycles on dynamic behaviour and feasibility. Additionally, there is no tuning procedure to design controllers that optimize the dynamic performance of plants, including the control system. In this context, this work presents an analysis to characterize the effects of recycles on the dynamic behaviour of plants, including how they affect the feasible operating region. Based on the previous analysis, a control methodology is also proposed to design the PWC strategy, explicitly addressing the dynamical phenomena of recycles in processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".