Title :
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
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;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.836190
