Toggle Main Menu Toggle Search

Open Access padlockePrints

Modeling and optimal control of fed-batch processes using control affine feedforward neural networks

Lookup NU author(s): Dr Zhihua Xiong, Dr Jie ZhangORCiD

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

Many fed-batch processes can be considered as a class of control-affine nonlinear systems. In this paper, a new methodology of neural network, called Control Affine Feed-forward Neural Network (CAFNN), is proposed. It can be trained easily. For constrained nonlinear optimization problems, it offers an effective and simple optimal control strategy by sequential quadratic programming in which the analytic gradient information can be computed directly. The proposed modeling and optimal control schemes are illustrated on an ethanol fermentation process. Compared with a general multilayer neural network, the nonlinear programming problem based on a CAFNN model is solved more accurately and efficiently.


Publication metadata

Author(s): Zhang J; Xiong Z

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the American Control Conference

Year of Conference: 2002

Pages: 5025-5030

ISSN: 0743-1619

Publisher: IEEE

URL: http://dx.doi.org/10.1109/ACC.2002.1025462

DOI: 10.1109/ACC.2002.1025462


Share