Record Details


Field	Value

Title	Optimal control of a fed-batch fermenter using parameterized data-driven models

Creator	Rani, K Yamuna

Subject	Artificial neural networks Fed-batch fermentation Linear model Optimal control Orthonormal polynomial approximations Parameterized data-driven modeling Quadratic model

Description	759-773 An optimal control approach is proposed for semi-batch processes based on parameterized data-driven (PDD) model structures. Orthonormally parameterized input trajectories, initial states and process parameters are inputs to the model, which predicts output trajectories in terms of Fourier coefficients. Two model structures (linear and quadratic) are incorporated into PDD modeling approach, and a previously proposed model structure of artificial neural networks (ANNs) is considered for comparison. Proposed PDD modeling approach using newly proposed model structures is capable of capturing nonlinear and time-varying behavior inherent in fed-batch systems fairly accurately, and results of operating trajectory optimization using all models are found to be comparable to the results obtained using exact first principles model.

Date	2008-10-22T07:32:35Z 2008-10-22T07:32:35Z 2008-10

Type	Article

Identifier	0022-4456 http://hdl.handle.net/123456789/2245

Language	en_US

Publisher	CSIR

Source	JSIR Vol.67(10) [October 2008]

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