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Lookup NU author(s): Dr Moritz von Stosch,
Dr Jie ZhangORCiD,
Dr Mark Willis
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© 2017 Nova Science Publishers, Inc. The performance of neural network approaches in process modelling, operation and design has been observed to improve significantly when they are combined with models derived from fundamental knowledge (e.g., first-principles). Mathematical models that combine neural network approaches with fundamental process knowledge are normally referred to as hybrid grey-box, hybrid neural (network), hybrid semi-parametric or just hybrid models. In this chapter, static and dynamic hybrid modelling concepts are introduced and their application in process monitoring and control are discussed. Two case studies are presented. The first, considers the development of a hybrid model for the monitoring of biomass in E.coli fermentations and the second, the optimal control of a polymerization reactor.
Author(s): von Stosch M, Zhang J, Willis M
Publication type: Book Chapter
Publication status: Published
Book Title: Artificial Neural Networks in Chemical Engineering
Print publication date: 01/01/2017
Acceptance date: 02/04/2016
Publisher: Nova Science Publishers, Inc.
Place Published: New York
Library holdings: Search Newcastle University Library for this item