A new approach for designing model-based indirect sensors

Author

Boillereaux, Lionel ; Flaus, Jean-Marie

Author_Institution

Dept. Genie des Procedes Alimentaire, ENITIAA, Nantes, France

Volume

8

Issue

4

fYear

2000

fDate

7/1/2000 12:00:00 AM

Firstpage

601

Lastpage

608

Abstract

We propose an approach to designing what we call a model-based indirect sensor. This methodology allows estimation of non-measurable variables from indirect measurements, by coupling a dynamical model of the process and an estimation algorithm. This method is especially developed with the aim of allowing a nonspecialist in process control to perform, with limited mathematical development, the state estimation of the processes he has to monitor or control. The main interest of this algorithm is its great simplicity of implementation. Moreover, we present a concept to tune this algorithm based on what we call numerical observability. The performance of this method is illustrated on a real bioprocess

Keywords

biotechnology; neural nets; process control; process monitoring; state estimation; bioprocess; dynamical model; estimation algorithm; indirect measurements; model-based indirect sensors; nonspecialist; numerical observability; Biological neural networks; Biosensors; Chemical and biological sensors; Industrial control; Mathematical model; Monitoring; Observability; Performance evaluation; Process control; State estimation;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/87.852906

Filename

852906