Abstract

Traditionally, fed-batch biochemical process optimization and control uses complicated off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability of a class of adaptive critic designs for online re-optimization and control of an aerobic fed-batch fermentor. Specifically, the performance of an entire class of adaptive critic designs, viz., heuristic dynamic programming, dual heuristic programming and generalized dual heuristic programming, was demonstrated to be superior to that of a heuristic random optimizer, on optimization of a fed-batch fermentor operation producing monoclonal antibodies

Department(s)

Electrical and Computer Engineering

Second Department

Computer Science

Keywords and Phrases

Adaptive Critic Designs; Batch Processing (Industrial); Biochemical Process; Dual Heuristic Programming; Dynamic Programming; Fed-Batch Fermentor; Feedforward Neural Nets; Fermentation; Heuristic Dynamic Programming; Monoclonal Antibodies; Process Control; Random Optimizer

International Standard Serial Number (ISSN)

1045-9227

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2001 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Full Text Link

Share

 
COinS