DocumentCode
1736865
Title
Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks
Author
Efe, Mehmet Önder ; Kaynak, Okyay
Author_Institution
Dept. of Electr. & Electron. Eng., Bogazici Univ., Istanbul, Turkey
fYear
1997
Firstpage
1211
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
Keywords
identification; neural nets; nonlinear dynamical systems; self-adjusting systems; unsupervised learning; classical neural networks; control strategies; dynamical neural networks; identification; inverse control strategy; nonlinear bioreactor plant; nonlinear dynamical systems; self-learning control; Artificial neural networks; Biological system modeling; Bioreactors; Control systems; Electronic mail; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear equations; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 1997. ISIE '97., Proceedings of the IEEE International Symposium on
Conference_Location
Guimaraes
Print_ISBN
0-7803-3936-3
Type
conf
DOI
10.1109/ISIE.1997.648914
Filename
648914
Link To Document