Systematic observability and detectablity analysis of industrial batch crystallizers

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Abstract

Motivated by the lack of hardware analysers for particle size distribution (PSD) and solute concentration measurements in industrial crystallizers, this work investigates the feasibility of designing alternative monitoring tools based on state observers. The observability and detectability properties of the discretized population balance equation accounting for crystal growth, attrition and agglomeration coupled with energy and solute mass balances are studied. A systematic methodology for sensor selection based on nonlinear observability and detectability principles is proposed and applied. Results are corroborated by a machine learning technique (the self-organizing map), leading to the fact that the solute concentration is distinguishable with temperature measurements, while the PSD is not. The results represent the starting point for future detector design where temperature measurements are used to infer composition, while the estimation of the PSD is done in "open loop" fashion.
Original languageEnglish
Pages (from-to)496-501
Number of pages6
JournalIFAC-PapersOnLine
Volume49
Issue number7
DOIs
Publication statusPublished - Jun 2016
Event11th IFAC International Symposium on Dynamics and Control of Process Systems, Including Biosystems (DYCOPS-CAB 2016) - Trondheim, Norway
Duration: 6 Jun 20168 Jun 2016
Conference number: 11
http://dycops2016.org/

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