Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks

Mehmet Onder Efe; Okyay Kaynak

Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks

Mehmet Onder Efe
, Okyay Kaynak

Bogazici University

Research output: Contribution to conference › Paper › peer-review

6 Citations (Scopus)

Abstract

In this study, the identification and control of a Bioreactor Plant using neural networks is considered with three different control strategies, namely, Inverse Control Strategy, Self-Learning Control and Dynamical Neural Units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.

Original language	English
Pages	1211-1215
Number of pages	5
Publication status	Published - 1997
Externally published	Yes
Event	Proceedings of the 1997 IEEE International Symposium on Industrial Electronics, ISIE. Part 3 (of 3) - Guimaraes, Portugal Duration: 7 Jul 1997 → 11 Jul 1997

Conference

Conference	Proceedings of the 1997 IEEE International Symposium on Industrial Electronics, ISIE. Part 3 (of 3)
City	Guimaraes, Portugal
Period	7/07/97 → 11/07/97

Cite this

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title = "Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks",

abstract = "In this study, the identification and control of a Bioreactor Plant using neural networks is considered with three different control strategies, namely, Inverse Control Strategy, Self-Learning Control and Dynamical Neural Units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.",

author = "Efe, \{Mehmet Onder\} and Okyay Kaynak",

year = "1997",

language = "English",

pages = "1211--1215",

note = "Proceedings of the 1997 IEEE International Symposium on Industrial Electronics, ISIE. Part 3 (of 3) ; Conference date: 07-07-1997 Through 11-07-1997",

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TY - CONF

T1 - Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks

AU - Efe, Mehmet Onder

AU - Kaynak, Okyay

PY - 1997

Y1 - 1997

N2 - In this study, the identification and control of a Bioreactor Plant using neural networks is considered with three different control strategies, namely, Inverse Control Strategy, Self-Learning Control and Dynamical Neural Units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.

AB - In this study, the identification and control of a Bioreactor Plant using neural networks is considered with three different control strategies, namely, Inverse Control Strategy, Self-Learning Control and Dynamical Neural Units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.

UR - https://www.scopus.com/pages/publications/0031383739

M3 - Paper

AN - SCOPUS:0031383739

SP - 1211

EP - 1215

T2 - Proceedings of the 1997 IEEE International Symposium on Industrial Electronics, ISIE. Part 3 (of 3)

Y2 - 7 July 1997 through 11 July 1997

ER -

Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks

Abstract

Conference

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