Plant-wide optimization of an ethanol plant using parametric hybrid models

Schweiger, Carl A.; Sayyarrodsari, B.; Bartee, Jim; Axelrud, Celso

doi:10.1109/cdc.2010.5717789

Cited by 1 publication

(1 citation statement)

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“…The integration of hybrid semi-parametric models into complex flowsheets for (bio)chemical processes and the resulting overall representation of the plant, is envisaged as a consequence of the publications by Fiedler and Schuppert (2008), Schweiger, Sayyar-Rodsari, Bartee, and Axelrud (2010). An integrated plantwide modeling approach provides several advantages, such as the possibility to plant-wide optimize the set-points or the opportunity to achieve better closedloop control performance.…”

Section: Concluding Remarks and Outlookmentioning

confidence: 99%

Hybrid semi-parametric modeling in process systems engineering: Past, present and future

Stosch¹,

Oliveira²,

Peres³

et al. 2014

Computers & Chemical Engineering

339

201

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Hybrid semi-parametric models consist of model structures that combine parametric and nonparametric submodels based on different knowledge sources. The development of a hybrid semi-parametric model can offer several advantages over traditional mechanistic or data-driven modeling, as reviewed in this paper. These advantages, such as broader knowledge base, transparency of the modeling approach and cost-effective model development, have been widely recognized, not only in academia but also in the industry.In this paper, the most common hybrid semi-parametric modeling and parameter identification techniques are revisited. Applications in the areas of (bio)chemical engineering for process monitoring, control, optimization, scaleup and model-reduction are reviewed. It is outlined that the application of hybrid semi-parametric techniques does not automatically lead into better results but that rational knowledge integration has potential to significantly improve model-based process operation and design.

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Section: Concluding Remarks and Outlookmentioning

confidence: 99%