Neuro-fuzzy generalized predictive control of boiler steam temperature

Authors:
Xiang-Jie Liu;Ji-Zhen Liu
Affiliations:
Department of Automation, North China Electric Power University, Beijing, P.R. China;Department of Automation, North China Electric Power University, Beijing, P.R. China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

Citing 3
Cited 0

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IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

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Abstract

Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modern power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network (NFGPC) is proposed in this paper, which consists of local GPCs designed using the local linear models of the neuro-fuzzy network. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant, in which much better performance than the traditional cascade PI controller or the linear GPC is obtained.