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          Institute: MPI für Dynamik komplexer technischer Systeme     Collection: Physical and Chemical Process Engineering     Display Documents



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ID: 239856.0, MPI für Dynamik komplexer technischer Systeme / Physical and Chemical Process Engineering
Methods of state estimation for particulate processes
Authors:Mangold, M.; Steyer, C.; Niemann, B.; Voigt, A.; Sundmacher, K.
Language:English
Publisher:Elsevier
Place of Publication:Amsterdam
Date of Publication (YYYY-MM-DD):2006
Title of Proceedings:16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering
Start Page:1191
End Page:1196
Name of Conference/Meeting:ESCAPE16 : European Symposium on Computer Aided Process Engineering
Place of Conference/Meeting:Garmisch-Partenkirchen, Germany
(Start) Date of Conference/Meeting
 (YYYY-MM-DD):
2006-07-09
End Date of Conference/Meeting 
 (YYYY-MM-DD):
2006-07-13
Review Status:Peer-review
Audience:Experts Only
Abstract / Description:Determining property distributions of particles online by measurement is difficult in many cases, especially if the particles are in the nanometre range. An alternative may be state estimation techniques, which use information from process simulations in addition to the measurement signals. Two examples of state estimators for particulate processes are presented in this contribution. The first one is an extended Kalman filter based on a population balance model. The second one is a bootstrap filter based on a Monte Carlo simulation.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Kai Sundmacher
Affiliations:MPI für Dynamik komplexer technischer Systeme/Physical and Chemical Process Engineering
MPI für Dynamik komplexer technischer Systeme/Process Synthesis and Process Dynamics
External Affiliations:Otto-von-Guericke-Universität Magdeburg
Fakultät für Verfahrens- und Systemtechnik
Institut für Verfahrenstechnik
Universitätsplatz 2
39106 Magdeburg
Identifiers:ISBN:0-444-52969-1
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