Extended Linear QDMC of a Gibbsite Crystalliser: A Simulation Study
Bibliographic record
Abstract
Abstract An extended linear quadratic dynamic matrix control (EQDMC) of a gibbsite crystallisation system is presented. The process model of the crystalliser is based on the conservation principles of mass and population balances, and kinetic relations including nucleation, growth, and agglomeration correlations. It is shown that the process is non‐linear with constraints and possesses interaction among its process variables. Practical concerns in crysallisation plants such as low flow rates and high magma densities that may lead to solids deposition and eventual line blocking are considered as the system's constraints. The controller is developed by combining extended linear dynamic matrix control (EDMC) and quadratic dynamic matrix control (QDMC) algorithms. Two types of control outputs are considered: controlled and associated variables. The capability of the controller in bringing the controlled variables to their setpoints while maintaining all process constraints within their limits is demonstrated via simulation. It is shown that increasing prediction horizon improves the control performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".