Hybrid process models for process optimisation, monitoring and control.
Hybrid models aim to describe different components of a process in different ways. This makes sense when the corresponding knowledge to be represented is different as well. In this way, the most efficient representations can be chosen and, thus, the model performance can be increased significantly. From the various possible variants of hybrid model, three are selected which were applied for important biotechnical processes, two of them from existing production processes. The examples show that hybrid models are powerful tools for process optimisation, monitoring and control.
Galvanauskas
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Institut für Bioengineering, Martin-Luther-Universität, Halle-Wittenberg, Germany. Andreas.Luebbert@iw.uni-halle.de
Simutis
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Lübbert
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D000465:Algorithms; D000818:Animals; D019149:Bioreactors; D018929:Cell Culture Techniques / Q000379:methods* / Q000639:trends; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D006801:Humans; D007221:Industry / Q000379:methods* / Q000639:trends; D008954:Models, Biological; D008991:Monitoring, Physiologic / Q000379:methods* / Q000639:trends; D016571:Neural Networks, Computer; D049490:Systems Biology / Q000379:methods / Q000639:trends