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2012 (Vol. 4, Issue: 14)
Article Information:

T-S Neural Network Model Identification of Ultra-Supercritical Units for Superheater Based on Improved FCM

Yunjuan Li and Yanjun Fang
Corresponding Author:  Yunjuan Li 

Key words:  Model identification, superheater, T-S neural network, ultra-supercritical units, , ,
Vol. 4 , (14): 2147-2152
Submitted Accepted Published
March 12, 2012 April 03, 2012 July 15, 2012
Abstract:

The study constructs the T-S neural network model for the superheater with multiple inputs and single output and presents an improved FCM algorithm aiming to solve the inputs’ space division problem. The function parameters of the Gaussian membership are obtained to identify the model structure and the recursive least squares method is adopted to identify model parameters. Simulations results show that the improved method has good performance in model identification and the identified models have preferable accuracy and generalization ability.
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  Cite this Reference:
Yunjuan Li and Yanjun Fang, 2012. T-S Neural Network Model Identification of Ultra-Supercritical Units for Superheater Based on Improved FCM.  Research Journal of Applied Sciences, Engineering and Technology, 4(14): 2147-2152.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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