Fed-batch dynamic optimization using generalized dual heuristic programming

Author

Iye, Mahesh S. ; Wunsch, Donald C., II

Author_Institution

Appl. Comput. Intelligence Lab., Texas Tech. Univ., Lubbock, TX, USA

Volume

5

fYear

1999

fDate

1999

Firstpage

3305

Abstract

Traditionally fed-batch biochemical process optimization and control uses complicated theoretical off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability, effectiveness, and economic potential of a simple phenomenological model for modeling, and an adaptive critic design, generalized dual heuristic programming, for online re-optimization and control of an aerobic fed-batch fermentor. The results are compared with those obtained using a heuristic random optimizer

Keywords

batch processing (industrial); feedforward neural nets; fermentation; learning (artificial intelligence); neurocontrollers; optimisation; process control; real-time systems; action learning; adaptive critic design; dual heuristic programming; dynamic optimization; fed-batch biochemical process; feedforward neural networks; fermentation; optimization; phenomenological model; process control; Adaptive control; Aerodynamics; Amino acids; Chemical engineering; Computational intelligence; Design optimization; Electronic mail; Inhibitors; Programmable control; Uniform resource locators;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.836190

Filename

836190