Bioreactor states estimation in the feedbatch process using differential neural networks

A. I. Cabrera; A. Poznyak; T. Poznyak

Bioreactor states estimation in the feedbatch process using differential neural networks

Research output: Contribution to journal › Conference article › peer-review

Abstract

For the feedbatch fermentation process (FFP) the estimation of the model's states is realized in two steps: ...rst, the observability conditions of the considered FFP-model are derived; second, the dynamic neural network technique is applied to obtain the current state estimations. The numerical simulations illustrate the effectiveness of the suggested approach.

Original language	English
Pages (from-to)	2906-2909
Number of pages	4
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	4
State	Published - 2000
Event	22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States Duration: 23 Jul 2000 → 28 Jul 2000

Keywords

Dynamic neural networks
Feedbatch fermentation process
Observability

Cite this

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title = "Bioreactor states estimation in the feedbatch process using differential neural networks",

abstract = "For the feedbatch fermentation process (FFP) the estimation of the model's states is realized in two steps: ...rst, the observability conditions of the considered FFP-model are derived; second, the dynamic neural network technique is applied to obtain the current state estimations. The numerical simulations illustrate the effectiveness of the suggested approach.",

keywords = "Dynamic neural networks, Feedbatch fermentation process, Observability",

author = "Cabrera, {A. I.} and A. Poznyak and T. Poznyak",

year = "2000",

language = "Ingl{\'e}s",

volume = "4",

pages = "2906--2909",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

note = "22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 23-07-2000 Through 28-07-2000",

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TY - JOUR

T1 - Bioreactor states estimation in the feedbatch process using differential neural networks

AU - Cabrera, A. I.

AU - Poznyak, A.

AU - Poznyak, T.

PY - 2000

Y1 - 2000

N2 - For the feedbatch fermentation process (FFP) the estimation of the model's states is realized in two steps: ...rst, the observability conditions of the considered FFP-model are derived; second, the dynamic neural network technique is applied to obtain the current state estimations. The numerical simulations illustrate the effectiveness of the suggested approach.

AB - For the feedbatch fermentation process (FFP) the estimation of the model's states is realized in two steps: ...rst, the observability conditions of the considered FFP-model are derived; second, the dynamic neural network technique is applied to obtain the current state estimations. The numerical simulations illustrate the effectiveness of the suggested approach.

KW - Dynamic neural networks

KW - Feedbatch fermentation process

KW - Observability

UR - http://www.scopus.com/inward/record.url?scp=0034440722&partnerID=8YFLogxK

M3 - Artículo de la conferencia

AN - SCOPUS:0034440722

SN - 0589-1019

VL - 4

SP - 2906

EP - 2909

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 23 July 2000 through 28 July 2000

ER -

Bioreactor states estimation in the feedbatch process using differential neural networks

Abstract

Keywords

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