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Taking advantage of the knowledge of top and bottom compositions of a distillation column, a dynamic neural network DNN is designed to identify the input-output relationship of the column. The weight-training algorithm is derived from a Lyapunov function. Based on this empirical model, a nonlinear H∞ controller is synthesized. The effectiveness of the control strategy is demonstrated using simulation results.

KEYWORDS

Distillation Column, Dynamic Neural Network, Nonlinear H∞ Control

Cite this paper

F. Li -Dynamic Neural Network Based Nonlinear Control of a Distillation Column,- Intelligent Control and Automation, Vol. 2 No. 4, 2011, pp. 383-387. doi: 10.4236-ica.2011.24043.





Autor: Feng Li

Fuente: http://www.scirp.org/



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