2003
DOI: 10.1016/s0098-1354(03)00043-7
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Hybrid model-based approach to batch-to-batch control of particle size distribution in emulsion polymerization

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Cited by 116 publications
(81 citation statements)
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“…The optimization recipe is formulated to minimize the squared deviation between the target final PSD and the one predicted by model (Doyle et al, 2003):…”
Section: Open-loop Control Strategymentioning
confidence: 99%
See 1 more Smart Citation
“…The optimization recipe is formulated to minimize the squared deviation between the target final PSD and the one predicted by model (Doyle et al, 2003):…”
Section: Open-loop Control Strategymentioning
confidence: 99%
“…Some published works have considered open-loop control of PSD in emulsion polymerization (Doyle et al, 2003;Doyle, 2002, 2003a;Sood, 2004). Using the open-loop strategy for PSD control is very sensitive to model uncertainties and disturbances.…”
Section: Introductionmentioning
confidence: 99%
“…The objective PSD was a bimodal distribution and the manipulated variable was a shot injection of emulsifier at 150 min. Doyle III et al (2003) proposed a hybrid model-based (first principles model along with a partial least squares to correlate PSD residuals) approach for batch-to-batch control of the PSD. They considered the manipulation of both surfactant feed rate (or concentration) and initiator feed rate to track a bimodal distribution.…”
Section: Psd Control In Emulsion Polymerizationmentioning
confidence: 99%
“…Lee and co-workers 11 presented the quadratic criterion-based iterative learning control (Q-ILC) approach for tracking control of batch processes based on a linear time-varying (LTV) tracking error transition model. Doyle and coworkers 12,13 used batch-to-batch optimization to achieve the desired particle size distribution (PSD) target in an emulsion polymerization reactor. A simplified theoretical model is used as predictor, but the prediction is corrected using an updated PLS model that relates the manipulated variables to the error from the theoretical model prediction and the measured distribution.…”
Section: Introductionmentioning
confidence: 99%