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Lookup NU author(s): Dr Zhihua Xiong, Dr Jie ZhangORCiD
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Many fed-batch processes can be considered as a class of control affine nonlinear systems. In this paper, a new type of neural network for modelling fed-batch processes, called as control affine feedforward neural network (CAFNN), is proposed. For constrained nonlinear optimal control of fed-batch processes, CAFNN offers an effective and simple optimal control strategy by sequential quadratic programming (SQP) where the gradient information can be computed directly from CAFNN. Thus the nonlinear programming problem can then be solved more accurately and efficiently. The proposed modelling and optimal control scheme are illustrated on a nonlinear system and a simulated fed-batch ethanol fermentation process. © 2003 Elsevier B.V. All rights reserved.
Author(s): Xiong Z, Zhang J
Publication type: Article
Publication status: Published
Journal: Neurocomputing
Year: 2004
Volume: 61
Issue: 1-4
Pages: 317-337
ISSN (print): 0925-2312
ISSN (electronic): 1872-8286
Publisher: Elsevier BV
URL: http://dx.doi.org/10.1016/j.neucom.2003.11.006
DOI: 10.1016/j.neucom.2003.11.006
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